index.json

[{"authors":["Chris Myers"],"categories":null,"content":"Chris Myers (Ph.D. in Electrical Engineering) is a Professor of Electrical and Computer Engineering at the University of Utah. He conducts research in design automation for asynchronous electronic circuits, analog/mixed-signal circuits, and genetic circuits for which he was named an IEEE Fellow in 2013. He has been working in the fields of systems and synthetic biology for more than 10 years which led to the development of the iBioSim software and the textbook Engineering Genetic Circuits. During this time, he has been heavily involved in standards, previously serving as an SBML editor and currently as a member of the SBOL advisory board.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"34919edc315bee274c8e35bd789eef66","permalink":"/author/chris-myers/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/chris-myers/","section":"authors","summary":"Chris Myers (Ph.D. in Electrical Engineering) is a Professor of Electrical and Computer Engineering at the University of Utah. He conducts research in design automation for asynchronous electronic circuits, analog/mixed-signal circuits, and genetic circuits for which he was named an IEEE Fellow in 2013.","tags":null,"title":"Chris Myers","type":"authors"},{"authors":["Dagmar Waltemath"],"categories":null,"content":"Dagmar is a professor of medical informatics and head of the data integration center at the University Medicine Greifswald, Germany. Her research focuses on biomedical data integration, including the development of strategies and tools for research data management, provenance and integration of biomedical data with clinical and health data. She has been actively involved in the development of SED-ML, SBML and the COMBINE Archive.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"7205ba8e21db41ced53b9065b078456b","permalink":"/author/dagmar-waltemath/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/dagmar-waltemath/","section":"authors","summary":"Dagmar is a professor of medical informatics and head of the data integration center at the University Medicine Greifswald, Germany. Her research focuses on biomedical data integration, including the development of strategies and tools for research data management, provenance and integration of biomedical data with clinical and health data.","tags":null,"title":"Dagmar Waltemath","type":"authors"},{"authors":["FieldML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"d058424f97a7facc730fee3645b5ca07","permalink":"/author/fieldml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/fieldml/","section":"authors","summary":"","tags":null,"title":"FieldML","type":"authors"},{"authors":["Michael Hucka"],"categories":null,"content":"Michael Hucka (Ph.D. in Computer Science and Engineering), staff scientist at Caltech. He has chaired the SBML effort by community consensus since 2003. Today he works on all aspects of SBML and is involved with BioModels.net activities.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"b68edea9815bb600f1181e12c85a2181","permalink":"/author/michael-hucka/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/michael-hucka/","section":"authors","summary":"Michael Hucka (Ph.D. in Computer Science and Engineering), staff scientist at Caltech. He has chaired the SBML effort by community consensus since 2003. Today he works on all aspects of SBML and is involved with BioModels.","tags":null,"title":"Michael Hucka","type":"authors"},{"authors":["Nicolas Le Novere"],"categories":null,"content":"Led a research group at the EMBL-EBI and the Babraham Institute. His interests included signal transduction and computational modeling of biological processes. His group participated to the development of BioModels Database and SBO. He was also involved in the development of SBML.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"b24df4054bde633a281a764e61abedca","permalink":"/author/nicolas-le-novere/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/nicolas-le-novere/","section":"authors","summary":"Led a research group at the EMBL-EBI and the Babraham Institute. His interests included signal transduction and computational modeling of biological processes. His group participated to the development of BioModels Database and SBO.","tags":null,"title":"Nicolas Le Novere","type":"authors"},{"authors":["Sarah Keating"],"categories":null,"content":"Sarah Keating is a Senior Research Engineer at UCL. She has worked as a member of the SBML Team since 2002 and has on four separate occasions served as an SBML Editor.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"ae45889010644698d44f5f741214a905","permalink":"/author/sarah-keating/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sarah-keating/","section":"authors","summary":"Sarah Keating is a Senior Research Engineer at UCL. She has worked as a member of the SBML Team since 2002 and has on four separate occasions served as an SBML Editor.","tags":null,"title":"Sarah Keating","type":"authors"},{"authors":["Augustin Luna"],"categories":null,"content":"Augustin Luna (PhD in Bioinformatics) is an Investigator at the Computational Biology Branch, National Library of Medicine (NLM) \u0026amp; Developmental Therapeutics Branch, National Cancer Institute (NCI), National Institutes of Health (NIH). The Luna lab conducts research to improve clinical outcomes, concentrated on areas of 1) network biology; specifically, mechanisms of external perturbation response using machine learning methods, and 2) standardizing biological data representations for integration. His group develops software tools for cancer drug discovery using network-guided approaches like SketchLay, TargetScore, CausalPath, textToKnowledgeGraph, CellMiner Cross-Database (CellMinerCDB), TumorComparer, NetBoxR, CellBox, drGT, DrugAgent, etc. He is also involved in the development of BioPAX and SBGN.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"715ebcf46cbb574936fe13a8d660d245","permalink":"/author/augustin-luna/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/augustin-luna/","section":"authors","summary":"Augustin Luna (PhD in Bioinformatics) is an Investigator at the Computational Biology Branch, National Library of Medicine (NLM) \u0026amp; Developmental Therapeutics Branch, National Cancer Institute (NCI), National Institutes of Health (NIH).","tags":null,"title":"Augustin Luna","type":"authors"},{"authors":["BioModels.net qualifiers"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2213b2e39ab4ec6a98c76c50bc1d3094","permalink":"/author/biomodels.net-qualifiers/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/biomodels.net-qualifiers/","section":"authors","summary":"","tags":null,"title":"BioModels.net qualifiers","type":"authors"},{"authors":["BioPAX"],"categories":null,"content":"BioPAX is a standard language that aims to enable integration, exchange and analysis of biological pathway data. It is expressed in OWL. The last specification is BioPAX Level 3. BioPAX development is coordinated by an elected editorial board and a Scientific Advisory Board. BioPAX is supported by many pathway database or processing tools. An API is available to help implementing support: Paxtools\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"787fbbe3c71cf9239ceb6f458059cae6","permalink":"/author/biopax/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/biopax/","section":"authors","summary":"BioPAX is a standard language that aims to enable integration, exchange and analysis of biological pathway data. It is expressed in OWL. The last specification is BioPAX Level 3. BioPAX development is coordinated by an elected editorial board and a Scientific Advisory Board.","tags":null,"title":"BioPAX","type":"authors"},{"authors":["CellML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"d1c7804625f120e2e19a26767fa7cab2","permalink":"/author/cellml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/cellml/","section":"authors","summary":"","tags":null,"title":"CellML","type":"authors"},{"authors":["CellML"],"categories":null,"content":"The CellML language is an XML markup language to store and exchange computer-based mathematical models. CellML is being developed by the Auckland Bioengineering Institute at the University of Auckland and affiliated research groups.\nThe latest stable specification is Version 2.0.\nCellML development is coordinated by an elected editorial board.\nAPIs are available to help implementing support: libCellML in C++, with Python and Javascript bindings available.\nMore information.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"ba80262a9bffc858c9acbef3e537b6dc","permalink":"/author/cellml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/cellml/","section":"authors","summary":"The CellML language is an XML markup language to store and exchange computer-based mathematical models. CellML is being developed by the Auckland Bioengineering Institute at the University of Auckland and affiliated research groups.","tags":null,"title":"CellML","type":"authors"},{"authors":["CNO"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"6cf368622a0e796312f52b8fc70bccd2","permalink":"/author/cno/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/cno/","section":"authors","summary":"","tags":null,"title":"CNO","type":"authors"},{"authors":["admin"],"categories":null,"content":"The \u0026ldquo;COmputational Modeling in BIology NEtwork\u0026rdquo; (COMBINE) is an initiative to coordinate the development of the various community standards and formats for computational models. By doing so, it is expected that the federated projects will develop a set of interoperable and non-overlapping standards covering all aspects of modeling in biology. The global COMBINE effort is led by the COMBINE Coordination Board.\nBuilding on the experience of mature projects, which already have stable specifications, software support, user-base and community governance, COMBINE will help foster or support fledgling efforts aimed at filling gaps or new needs. As those efforts mature, they may become part of the core set of COMBINE standards.\nOne of the initial activities of COMBINE is to coordinate the organization of scientific and technical events common to several standards. Those events, as others related to our field of research are gathered in a calendar.\nTo discuss the goals, organization and operation of COMBINE, subscribe to COMBINE discuss mailing list.\nTo report issues about the co.mbine.org website, send a mail to combine-support @ googlegroups.com\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"/author/combine/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine/","section":"authors","summary":"The \u0026ldquo;COmputational Modeling in BIology NEtwork\u0026rdquo; (COMBINE) is an initiative to coordinate the development of the various community standards and formats for computational models. By doing so, it is expected that the federated projects will develop a set of interoperable and non-overlapping standards covering all aspects of modeling in biology.","tags":null,"title":"COMBINE","type":"authors"},{"authors":null,"categories":null,"content":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2021 will be a workshop-style online event with oral presentations, breakout sessions and tutorials. The five meeting days will include talks about the COMBINE standards and associated or related standardization efforts, presentations of tools using these standards, breakout sessions for detailed discussions as well as tutorials.\nCOMBINE 2021 will be an online (virtual) meeting from October 11th (Monday) to October 15th (Friday). It will provide a schedule which takes into account all time zones around the world, a real 24 hour conference. The meeting will be free of charge.\nAgenda The latest agenda is available on Sched at https://combine2021.sched.com. The page is password protected (to protect access to the links for video conferencing sessions), and full details will be sent to registered attendees.\nYou can download a pdf of the provisional agenda here (subject to change; all times in UTC).\nThe recordings of the COMBINE 2021 presentations are available here: https://www.dropbox.com/sh/hx9600dl53r68fr/AAB7YZV9ZyN4Ta193OV7q25Ba?dl=0.\nThe times of the invited speaker presentations can be seen below (all times in UTC).\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"4442bde51cbc79b0732be28427ddc5c8","permalink":"/author/combine-2021/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2021/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2021 will be a workshop-style online event with oral presentations, breakout sessions and tutorials.","tags":null,"title":"COMBINE 2021","type":"authors"},{"authors":null,"categories":null,"content":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2022 will be a workshop-style event with oral presentations, breakout sessions and tutorials. The three meeting days will include talks about the COMBINE standards and associated or related standardization efforts, presentations of tools using these standards, breakout sessions for detailed discussions as well as tutorials.\nCOMBINE 2022 will be an in-person meeting organised as a satellite to the ICSB 2022 meeting in Berlin.\nThe daily welcomes, wrap-up and the COMBINE forum will be streamed online. Please register via the following link for the stream: (was hu-berlin.zoom.us/meeting/register/u5EocOGoqzgiE9LPwbHLtC-m_6UTn7LCXx6X)\nThe COMBINE 2022 meeting is organised by Dagmar Waltemath and Matthias König.\nOverview COMBINE Community meet-up Two days of breakout sessions and tutorials related to COMBINE standards\nThus 6th \u0026amp; Fri 7th Oct, 8:30am-6pm at Humboldt University of Berlin, Philippstraße 13, House 4\nAll attendees can suggest breakout sessions for detailed discussions of certain aspects of one or several of the COMBINE standard(s), discussions on metadata and semantic annotations (format-specific or overarching), discussions on the application and implementations of the COMBINE standards, or any other topic relevant for the COMBINE community.\nWe also solicit applications to host tutorials on tools, standards or resources (or any other topic) which would be relevant for the COMBINE community (see Topics of Interest below). The link to submit suggestions for breakout sessions or tutorials is here.\nCOMBINE Forum Single track session with invited and submitted talks\nSat 8th Oct, 8am-1pm at Humboldt University of Berlin, Philippstraße 13, House 4\nHow to get there? COMBINE2022 is located at Humboldt University of Berlin, Philippstraße 13, House 4\nThe main entry is at Philippstraße 13. The main event site is in House 4, where the daily welcomes, wrap-ups and the COMBINE Forum will take place. In addition, some breakouts will take place in House 20 and House 18. Please see the following plan for details:\nAgenda Thursday Oct 6 - COMBINE Community meet-up Day 1          8:30am Welcome (Matthias König, House 4, Lecture Hall)   9am Breakouts \u0026amp; Tutorials 1  Breakouts:  - Room 2 (House 4, 012a): SEP 55 (Prashant Vaidyanathan)  - Room 1 (House 4, Lecture Hall): SED-ML Level 2: Proposals and Requirements (Lucian Smith)   10:30am Break / Coffee   11am Breakouts \u0026amp; Tutorials 2 Tutorial: - Room 3 (House 18, Maut Menten): CovidGraph: Interfaces and Usage (Lea Gütebier)  Breakouts:  - Room 2 (House 4, 012a): Parametric SVG for SBOL Visual (Thomas Gorochowski)  - Room 1 (House 4, Lecture Hall): SED-ML Level 2: Proposals and Requirements   12:30pm Lunch (self organized)   2pm Breakouts \u0026amp; Tutorials 3Tutorial:  - Room 3 (House 18, Maud Menten): Clinical trial simulations with the Jinkō modeling platform  Breakouts:  - Room 2 (House 4, 012a): SBOL 3.1 (Gonzalo Vidal) - Room 1 (House 4, Lecture hall): Curating models and simulations for BioSimulations (David Nickerson) - online: Protocol Activity Modeling Language Standard Working Group (Daniel Bryce)   3:30pm Break / Coffee   4pm Breakouts \u0026amp; Tutorials 4 Breakouts:  - Room 2 (House 4, 012a): Representation of Site-Variant Libraries (James Diggans)  - Room 1 (House 4, Lecture Hall): VSCode-Antimony: A Smart Editor for Developing Models in Systems Biology (Joe Hellerstein/Herbert Sauro)  - online: Protocol Activity Modeling Language Standard Working Group   5:30pm Wrap-up (House 4, Lecture Hall)     Friday Oct 7 - COMBINE Community meet-up Day 2          8:30am Welcome (Matthias König, House 4, Lecture Hall)   9am Breakouts \u0026amp; Tutorials 5 Tutorial: - Room 1 (House 4, Lecture Hall): Morpheus: Multi-scale, Multi-cellular, Spatio-temporal Modeling with Hands-on for Your Own Projects  Breakouts:  - Room 3 (House 20, Seminar Room 1): Managing RDF Packages (Jacob Beal)  - Room 2 (House 4, 012a): FROG Analysis - a community standard to foster reproducibility and curation of constraint-based models (Rahuman Sheriff)  - Room 4 (House 20, Seminar Room 2): Similarity Computation of Small Molecule Names (Lukrécia Mertová)   10:30am Break / Coffee   11am Breakouts \u0026amp; Tutorials 6 Breakouts:  - Room 3 (House 20, Seminar Room 1): SBOL Examples (Prashant Vaidyanathan)  - Room 2 (House 4, 012a): FAIRness assessment of COMBINE archives (Irina Balaur, Dagmar Waltemath)  - Room 1 (House 4, Lecture Hall): MultiCellML \u0026ndash; a \u0026ldquo;to-be\u0026rdquo; Multi-cellular Modelling language (Jörn Starruß) - Room 4 (House 20, Seminar Room 2): SBML FBC Package Finalization (Matthias König)   12:30pm Lunch (self organized)   2pm Breakouts \u0026amp; Tutorials 7 Tutorial:  - Room 1 (House 4, Lecture Hall): Creating reproducible biochemical modeling workflows in Python (Part 1)  Breakouts:  - Room 3 (House 20, Seminar Room 1): RNA Working Group Discussions (Thomas Gorochowski)  - Room 2 (House 4, 012a): FAIRness assessment of COMBINE archives  - Room 4 (House 20, Seminar Room 2): MultiCellML \u0026ndash; a \u0026ldquo;to-be\u0026rdquo; Multi-cellular Modelling language (Jörn Starruß)  - online: Protocol Activity Modeling Language Standard Working Group (Daniel Bryce)   3:30pm Break / Coffee   4pm Breakouts \u0026amp; Tutorials 8 Tutorial: - Room 1 (House 4, Lecture Hall): Creating reproducible biochemical modeling workflows in Python (Part 2)  Breakouts:  - Room 3 (House 20, Seminar Room 1): RNA Working Group Discussions  - Room 4 (House 20, Seminar Room 2): \u0026ldquo;Data Hazards: framework for thinking ethics in computational systems biology (Susana Roman Garcia)\u0026rdquo;  - Room 2 (House 4, 012a): SBGN general discussion (Adrien Rougny)  - online: Protocol Activity Modeling Language Standard Working Group (Daniel Bryce)   5:30pm Wrap-up (House 4, Lecture Hall)             2:30pm - 5.00pm - different location: Workshop on statistical inference for dynamical models, PETab (Jan Hasenauer, Daniel Weindl)     Saturday Oct 8 - COMBINE Forum          8am Poster Session / Coffee   8:45am Welcome (Dagmar Waltemath and Matthias König)   9am Invited Talk F.A.I.R. Bayesian Workflows and Model Citation Analysis  Nicole Radde, University of Stuttgart   9:30am Contributed TalksFROG Analysis - a community standard to foster reproducibility and curation of constraint-based models\tRahuman Malik Sheriff BioCypher: an ontology-driven framework for flexible harmonisation of large-scale biomedical knowledge graphs\tSebastian Lobentanzer Implementing Safe Cross-Document RDF References\tJacob BealThe Protocol Activity Modeling Language\tJacob Beal   10:30am Poster Session / Coffee   11am Invited Talk  Documentation of simulation studies \u0026mdash; beyond reproducibility  Adelinde Uhrmacher, Institute for Visual and Analytic Computing, University Rostock  By storing information about a simulation study within a provenance graph the stored information becomes queryable and the dependencies between different modeling and experimenting activities and the used or generated entities become visually accessible. Combined with explicit unambiguous model and simulation experiment specifications such a documentation enhances the reproducibility of the simulation study and the credibility of its products. However, as every documentation of a simulation study, it requires additional effort by the modeler. Therefore, to make the most out of the documentation, how can it be used beyond being a source of information for the modeler about the current or a previous simulation study? In this talk we will discuss the potential, challenges, and experiences in using information stored in a provenance graph to generate and execute simulation experiments during simulation studies automatically.   11:30am Contributed Talks FAIRDOM: Promoting and Supporting FAIR Data and Model Management in Systems Biology\tOlga KrebsMeDaX - our vision for bioMedical Data eXploration\tJudith WodkeMorpheus: Multi-scale, Multi-cellular, Spatio-temporal Modeling Made Easy\tJörn StarrußAnalyze Parameter Space for Rule-based Models with Simmune AnalyzerFengkai Zhang   12:30pm Poster Session / Coffee   1pm Adjourn    Attendees 86 participants have registered for COMBINE2022 so far.    Name Affiliation Attendance     Mihail Anton Chalmers University of Technology Friday 7th OctoberCOMBINE Archive and OMEX, FROG, ModeleXchange, Personalized Medicine, SBGN   Lara BRUEZIERE Novadiscovery Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBGN, SBML, SED-ML   Irina Balaur University of Luxembourg Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, SBGN   Jacob Barhak Jacob Barhak Analytics Friday 7th October, Saturday 8th OctoberModeleXchange, SBML   Bryan Bartley Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Florian Bartsch Institut für theoretische Biologie, Humboldt-Universität zu Berlin Thursday 6th October, Friday 7th OctoberPersonalized Medicine, SBML   Jacob Beal Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Frank Bergmann Heidelberg University, BioQUANT / COS Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, PEtab, SBGN, SBML, SED-ML   Michael Blinov UConn Health Friday 7th October, Saturday 8th OctoberBioPAX, COMBINE Archive and OMEX, ModeleXchange, PEtab, SBGN, SBML, SED-ML   Lutz Brusch Technische Universität Dresden Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, PEtab, MultiCellML, MorpheusML, SBML-Spatial   Daniel Bryce SIFT, LLC. Thursday 6th October, Friday 7th October, Saturday 8th October-   Lukas Buecherl University of Colorado Boulder Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, Personalized Medicine, SBML, SBOL, SBOL Visual, SED-ML   Zsófia Bujtár Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Berlin) Friday 7th October, Saturday 8th OctoberSBGN, SBML, DDE-BIFTOOL   Famke Bäuerle University of Tuebingen Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, Personalized Medicine, SBGN, SBML, SED-ML   Jeremy Cahill Metamer Labs Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, NeuroML, Personalized Medicine, PEtab, SBGN, SBML, SBOL, SBOL Visual, SED-ML   Marie Coutelier Paris Brain Institute -CellML, COMBINE Archive and OMEX, NeuroML, Personalized Medicine   Tobias Czauderna University of Applied Sciences Mittweida Friday 7th October, Saturday 8th OctoberSBGN   James Diggans Twist Bioscience Thursday 6th OctoberSBOL, SBOL Visual   Andreas Dräger Eberhard Karls Universität Tübingen Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, SBGN, SBML, SED-ML   Dorotea Dudas HITS gGmbH Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Ibrahim Dulijan stevens.edu Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML, SBOL, SBOL Visual   Longxuan Fan University of Washington Thursday 6th OctoberSBML   Fabian Fröhlich Harvard Medical School Friday 7th October, Saturday 8th OctoberBioPAX, PEtab, SBML, SED-ML   Alan Garny University of Auckland Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, SED-ML   Robert T. Giessmann Institute for globally distributed open research and education (IGDORE) -BioPAX, COMBINE Archive and OMEX, SBML, SBOL, SBOL Visual, SED-ML, thermodynamic data, openTECR   Mose Giordano UCL Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Thomas Gorochowski University of Bristol Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Alexander Gower Chalmers University of Technology Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, PEtab, SBGN, SBML, SED-ML   Niklas Gröne Universität Konstanz Thursday 6th October, Friday 7th October, Saturday 8th October-   Roy Gusinow University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML, PEtab, SBML   Lea Gütebier Department of Medical Informatics, Institute for Community Medicine, University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, Personalized Medicine, SBML, SED-ML   Jan Hasenauer University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberModeleXchange, Personalized Medicine, PEtab, SBGN, SBML, SED-ML   Joseph Hellerstein eScience Institute, University of Washington Thursday 6th OctoberSBML, SED-ML   Joseph Hellerstein University of Washington Thursday 6th OctoberPEtab, SBML, SED-ML   Ron Henkel University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, ModeleXchange, SBGN, SBML, SBOL, SED-ML   Henning Hermjakob EMBL-EBI Friday 7th October, Saturday 8th OctoberBioPAX, COMBINE Archive and OMEX, FROG, ModeleXchange, SBML   Sebastian Höpfl Institute for Systems Theory and Automatic Control (IST) Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, PEtab, SBML   Johann Fredrik Jadebeck IBG-1 Forschungszentrum Jülich Thursday 6th October, Saturday 8th OctoberFROG, SBML   João Júnior Centro de Tecnologia Canavieira Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, ModeleXchange, Personalized Medicine, SED-ML   Miroslav Kratochvíl Luxembourg Centre for Systems Biomedicine Saturday 8th OctoberFROG, SBML   Olga Krebs Heidelberg Institute for Theoretical Studies Thursday 6th October, Friday 7th October, Saturday 8th OctoberPersonalized Medicine, PEtab, SBML, SBOL, SBOL Visual, SED-ML   Adrian Köller Institut für theoretische Biologie, Humboldt-Universität zu Berlin Thursday 6th October, Friday 7th OctoberSBML   Matthias König Humboldt-University Berlin Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, Personalized Medicine, PEtab, SBML, SED-ML   Paul Lang University of Oxford; Julia Computing Saturday 8th OctoberPersonalized Medicine, PEtab, SBML   Eva Liu University of Washington Bioengineering Sys-Bio Lab Thursday 6th October-   Sebastian Lobentanzer University Hospital Heidelberg Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, Personalized Medicine, PEtab, SBGN, SBML   Augustin Luna Harvard Medical School Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, SBGN   Karin Lundengård Auckland Bioengineering Institute Thursday 6th October, Friday 7th October-   Steve Ma NVIDIA Thursday 6th OctoberSBML   Simon Merkt University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML, PEtab, SBGN, SBML   Lukrécia Mertová Heidelberg Institute for Theoretical Studies HITS gGmbH Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, ModeleXchange, Personalized Medicine, SBML, SBOL   Goksel Misirli Keele University Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Ion Moraru UConn Health Thursday 6th October, Friday 7th OctoberCOMBINE Archive and OMEX, SBML, SED-ML   Sébastien Moretti SIB Swiss Institute of Bioinformatics Thursday 6th October, Friday 7th OctoberSBML   Chris Myers University of Colorado Boulder Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual, SBML, SED-ML   Tung Nguyen EMBL-EBI Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, Personalized Medicine, PEtab, SBGN, SBML, SED-ML   David Nickerson Auckland Bioengineering Institute, University of Auckland Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, PEtab, SED-ML   Dilan Pathirana University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML   Clemens Peiter IRU MLS, LIMES, University of Bonn Thursday 6th October, Friday 7th OctoberPEtab, SBGN, SBML   Sathish Periyasamy Queensland Brain Institute Friday 7th October, Saturday 8th OctoberCellML, NeuroML, Personalized Medicine, SBGN, SBML   Fronth Nyus Pi Quantum4Life Sensonomiqs Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, NeuroML, SBML, SBOL   Veronica Porubsky University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML   Nicole Radde University of Stuttgart Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, PEtab, SBML   Karthik Raman Indian Institute of Technology Madras Thursday 6th October, Friday 7th October, Saturday 8th OctoberFROG   Gianmarco Rasi - Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Susana Roman Garcia University of Edinburgh Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, ModeleXchange, NeuroML, Personalized Medicine, PEtab, SBGN, SBML, SBOL, SBOL Visual, SED-ML   Adrien Rougny Independent researcher (former AIST) Friday 7th October, Saturday 8th OctoberSBGN   Herbert Sauro University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, SBML, SED-ML   Falk Schreiber University of Konstanz Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBGN, SBML, SBOL Visual   James Scott-Brown University of Edinburgh Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Vinoo Selvarajah iGEM Foundation Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Woosub Shin Auckland Bioengineering Institute, University of Washington -SBML   Lucian Smith University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, FROG, PEtab, SBML, SED-ML   Jörn Starruß TU Dresden Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML, MultiCellML   Melanie Stefan Medical School Berlin Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, SBGN, SBML   Abel Szkalisity University of Helsinki Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, SBML   Baishakhi Tikader Indian Institute of Bombay, India Friday 7th OctoberSBML   Krishna Kumar Tiwari EMBL-EBI Thursday 6th October, Friday 7th October, Saturday 8th OctoberFROG, ModeleXchange, Personalized Medicine, SBGN   Matej Troják Masaryk university Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Adelinde Uhrmacher University of Rostock Saturday 8th OctoberCellML, COMBINE Archive and OMEX, SBGN, SBML, SED-ML   Prashant Vaidyanathan Oxford Biomedica Thursday 6th October, Friday 7th OctoberSBOL   Paola Vera-Licona UConn Health Friday 7th OctoberBioPAX, Personalized Medicine, SBML   Gonzalo Vidal ICOS, Newcastle University Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Dagmar Waltemath University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, SBML, SED-ML, FAIR model indicators   Daniel Weindl Helmholtz Munich Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML, SED-ML   St. Elmo Wilken Heinrich Heine University Saturday 8th October-   Pia Wilsdorf University of Rostock Saturday 8th OctoberCOMBINE Archive and OMEX, PEtab, SED-ML   Fengkai Zhang NIAID/NIH Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, SBGN, SBML, SED-ML   kristina gruden NIB Saturday 8th OctoberCellML, SBGN, SBML, SBOL    ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"74287d7c249e8ab67f0df8980603e2a8","permalink":"/author/combine-2022/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2022/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2022 will be a workshop-style event with oral presentations, breakout sessions and tutorials.","tags":null,"title":"COMBINE 2022","type":"authors"},{"authors":null,"categories":null,"content":"NEWS October 4:\n 78 attendees 9 breakouts, 8 tutorials, 8 talks, 11 lightning talks, and posters.  The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2023 was a workshop-style event hosted at the Center for Cell Analysis and Modeling at the University of Connecticut School of Medicine, Farmington, CT, USA. The meeting was held in October 2023, closely aligned with the dates of the International Conference on Systems Biology (ICSB) October 8-12 in Hartford, CT. Tutorials at the last day (Sunday October 8th) took place at the ICSB 2023 venue - in the convention center. The meeting days included talks about the COMBINE standards and associated or related standardization efforts, presentations of tools using these standards, breakout sessions for detailed discussions as well as tutorials. There were no dedicated poster sessions, but participants were encouraged to bring posters - poster boards were provided next to meeting places. Some time each day was left for community discussion and wrap-ups of breakouts and advertisements for following breakouts. It was primarily an in-person meeting, with individual breakout sessions responsible for enabling remote participation as needed.\nLocal organizers were Michael Blinov (blinov@uchc.edu) and Ion Moraru (moraru@uchc.edu).\nStudents may apply for a travel support from NSF!!! Link is on the LEFT! -- A tentative schedule Note that many events are scheduled somewhat spontaneously at these events; keep an eye out here or on the COMBINE slack for last-minute changes and additions.\nWorkshop Location COMBINE 2023 took place at the Center for Cell Analysis and Modeling (CCAM) in Farmington, CT. COMBINE 2023 took place in the Cell and Genome Sciences building, at 400 Farmington Ave, Farmington, CT 06119.\nArrival and Transportation The closest airport is the Bradley International Airport (BDL). The recommended transportation is to take Uber/Lyft to 400 Farmington Ave, Farmington, CT. It takes about 25 minutes and costs about $40. You may rent a car at BDL - all parking at the workshop location and hotel are free. A less expensive but long travel from BDL is to take Bradley Flyer Bus (#30) from BDL to Central Row North Side at Old State House Station, and then take a bus 66T from Main St \u0026amp; Asylum St to 400 Farmington Ave. It takes 1 to 3 hours depending on schedules.\nAccomodations and meals The closest hotel to the CCAM is the Homewood Suites by Hilton Hartford-Farmington at 2 Farm Glen Boulevard, Farmington, Connecticut, 06032; it\u0026rsquo;s 7 minutes walk between there and the venue. A University rate of $154/night will be provided upon request. There are more hotels in the area, but any other hotel will require a car.\nThe hotel serves hot breakfast. There is a Butchers and Bakers restaurant 15 minutes walk, but no food stores within walking distance. We will serve food at the venue, depending on the sponsors it may be free or for a nominal fee.\nAttendees 76 registered participants as of October 2\n   Name  Affiliation Attendance in person Interested  Projects     Alan Garny  University of Auckland remotely SED-ML, OMEX, COMBINE;CellML;Ontologies (SBO, KiSAO)  libOpenCOR (https://opencor.ws/libopencor/ ) and OpenCOR (https://opencor.ws/ )   Alex Patrie  UConn Health Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;CellML;Multicellular modeling  -   Amin Boroomand  Woods Hole institute Oct 5 Oct 6 Oct 7 Oct 8 SBML;Multicellular modeling  -   Amir Mahari  University of Arkansas Oct 5 Oct 6 Oct 7 Oct 8 SBML;SBGN;Multicellular modeling  I focus on the modeling and simulation of intercellular signaling pathways within melanoma cancer cells. This study holds significance due to the intricate nature of signaling cascades that regulate various cellular processes in melanoma progression. To facilitate this investigation, I employ PySB (Python Systems Biology), a powerful computational framework designed for creating, simulating, and analyzing mathematical models of biochemical systems. PySB\u0026rsquo;s modular and user-friendly nature enables me to construct complex models of intercellular signaling, incorporating factors such as ligand-receptor interactions, protein phosphorylation, and gene expression. Through PySB\u0026rsquo;s simulation capabilities, I can dynamically analyze the behavior of these pathways under different conditions, gaining insights into the underlying mechanisms that drive melanoma growth and metastasis. Ultimately, this research using PySB contributes to an enhanced understanding of melanoma biology, potentially paving the way for novel therapeutic interventions and personalized treatment strategies in combating this aggressive form of cancer.   Aniruddha Chattaraj  Harvard University Oct 5 Oct 6 Oct 7 Oct 8 SED-ML, OMEX, COMBINE;Multicellular modeling  Modeling of multivalent protein clustering, statistical analysis of cluster properties and visualization. Developer of MolClustPy. Interested in multi-scale modeling, specially problems related to biofilm formation. Software - Bionetgen, Virtual Cell, SpringSaLaD, LAMMPS, Python   Augustin Luna  Harvard Medical School remotely SBGN;BioPAX  https://www.pathwaycommons.org https://biofactoid.org/   Bartholomew Jardine  University of Washington remotely SBML;SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO);Multicellular modeling  Software tools for creating, editing, and simulating SBML complient modelss   Carolus Vitalis  University of Colorado Boulder  SBOL, SBOL visual;Multicellular modeling  -   Chris Myers  University of Colorado Boulder remotely SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual  SynBioHub/SynBioSuite/iBioSim   Dagmar Waltemath  University Medicine Greifswald remotely SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO)  -   Dan Vasilescu  UCHC Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;BioPAX;Ontologies (SBO, KiSAO)  -   Daniel Ajuzie  undergraduate Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual;CellML;Ontologies (SBO, KiSAO);Multicellular modeling  Ensemble Modeling; Model Optimization and Calibration   David Nickerson  Auckland Bioengineering Institute, University of Auckland remotely SED-ML, OMEX, COMBINE;CellML;Ontologies (SBO, KiSAO);OMEX Metadata; FAIR indicators for models; repositories  -   Diego Jahn  TUD Dresden University of Technology, Center for Information Services and High Performance Computing (ZIH) remotely Multicellular modeling  MorpheusML, MorpheusML Model Repository (https://morpheus.gitlab.io ), Multicellular Modeling   Difei Tang  University of Pittsburgh Oct 5 Oct 6 Oct 7 Oct 8 SBML;BioPAX;SBOL, SBOL visual;Ontologies (SBO, KiSAO)  GUI for DySE framework   Dilan Pathirana  University of Bonn Oct 5 Oct 6 Oct 7 Oct 8 SBML;Ontologies (SBO, KiSAO);Multicellular modeling;PEtab  PEtab ( https://github.com/PEtab-dev/petab ). PEtab for model selection ( https://github.com/PEtab-dev/petab_select ). Model collection for benchmarking studies ( https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab/ ).   Edwin Moses Appiah  Center for Cell Analysis and Modelling Oct 5 Oct 6 Oct 7 Oct 8 CellML;Multicellular modeling  -   Egils Stalidzans  PhD Oct 5 Oct 6 Oct 7 Oct 8 SBML;SBOL, SBOL visual  ODE-based kinetic modeling, constraint based stoichiometric modeling   Elebeoba May  University of Wisconsin-Madison Oct 5 Oct 6 Oct 7 Oct 8 SBML;Multicellular modeling;Visualization  biochemical/bionetwork ODE models (metabolism, signal transduction, gene networks), multiscale models of host-pathogen systems, multiscale models of microbial communities, modeling synthetic bio systems   Eran Agmon  UConn Health Oct 5 Oct 6 Oct 7 Oct 8 SED-ML, OMEX, COMBINE;Multicellular modeling  Vivarium: https://vivarium-collective.github.io   Fengkai Zhang  NIH Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN  Simmune (https://simmune.org/simmune/i_sim.html ), rule-based modeling and libSBML-multi   Frank T. Bergmann  BioQUANT, Heidelberg University Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN  COPASI (https://copasi.org ), basico (https://basico.readthedocs.io/ ), libSBML / libSEDML / libCombine   Gaoxiang Zhou  University of Pittsburgh Oct 5 Oct 6 Oct 7 Oct 8 SBML;BioPAX;SBOL, SBOL visual;CellML;Multicellular modeling  https://github.com/pitt-miskov-zivanov-lab, https://melody-biorecipe.readthedocs.io   Gerhard Mayer  HITS (Heidelberg Institute for Theoretical Studies) gGmbH, Heidelberg remotely SED-ML, OMEX, COMBINE;Multicellular modeling  EDITH (Ecosystem Digital Twins in Healthcare); https://www.edith-csa.eu   Herbert M Sauro  University of Washington remotely SBML;SED-ML, OMEX, COMBINE;Multicellular modeling  SBML, roadrunner etc   Ion Moraru  UConn Health Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;model credibility  VCell, BioSimulations, BioSimulators   Jacob Beal  Raytheon BBN Oct 5 Oct 6 Oct 7 Oct 8 SBOL, SBOL visual  -   James A. Glazier  Indiana University Oct 5 Oct 6 Oct 7 Oct 8 Multicellular modeling  CompuCell3D, Virtual Cornea, IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics   Jessica Yu  Allen Institute for Cell Science remotely SED-ML, OMEX, COMBINE;Multicellular modeling  agent-based modeling, cloud-based simulation and analysis workflows   Jim Schaff  Contractor - UConn Health Oct 5 Oct 6 Oct 7 Oct 8 SED-ML, OMEX, COMBINE;Multicellular modeling  Virtual Cell Project (vcell.org), Reproducible Biological Modeling (reproduciblebiomodels.org)   John Gennari  University of Washington Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;BioPAX;CellML;Ontologies (SBO, KiSAO)  Center for Reproducible Biomedical Modeling   Juliano Ferrari Gianlupi  Postdoctoral Scholar, UTHSC Oct 5 Oct 6 Oct 7 SBML;CellML;Multicellular modeling  PhenoCellPy https://www.biorxiv.org/content/10.1101/2023.04.12.535625v2.abstract; Translating PhysiCell specification into CompuCell3D simulation https://github.com/JulianoGianlupi/pcxml2cc3d   Jörn Starruß  Technische Universität Dresden, Germany remotely SBML;SED-ML, OMEX, COMBINE;CellML;Multicellular modeling  MorpheusML, https://morpheus.gitlab.io, Multicellular modeling, https://MultiCellML.org, SBML-Spatial, PEtab-MS, https://gitlab.com/fitmulticell/fit   Jürgen Pahle  Heidelberg University Oct 5 Oct 6 Oct 7 Oct 8 -  Copasi, CoRC   Lara Bruezière  Novadiscovery remotely SBML;SED-ML, OMEX, COMBINE;SBGN  Jinko software - collaborative clinical trial simulation platform   Lea Seep  University Bonn, IRU-MLS Oct 5 Oct 6 Oct 7 Oct 8 SBML;Ontologies (SBO, KiSAO)  -   Leslie Loew  U. Conn. School of Medicine Oct 5 Oct 6 SBML;SED-ML, OMEX, COMBINE;Multicellular modeling  Virtual Cell (aka VCell); SpringSaLaD   Lucian Smith  University of Washington Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO);Multicellular modeling  Antimony, Roadrunner, Tellurium, SBML, SED-ML   Luis Fonseca  University of Florida remotely SBML;SBGN;CellML;NeuroML;Multicellular modeling;ABM  -   Lukas Buecherl  University of Colorado Boulder remotely SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual  -   Lutz Brusch  Technische Universität Dresden, Germany remotely Multicellular modeling  Multicellular modeling, https://MultiCellML.org, MorpheusML, https://morpheus.gitlab.io, SBML-Spatial, PEtab-MS, https://gitlab.com/fitmulticell/fit, FAIRSPACE   Maren Philipps  University of Bonn Oct 5 Oct 6 Oct 7 Oct 8 -  PEtab, pyPESTO   Mauro Silberberg  Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, y CONICET - Instituto de Física de Buenos Aires (IFIBA). Buenos Aires, Argentina remotely SBML;SED-ML, OMEX, COMBINE;CellML;NeuroML  poincaré (github.com/maurosilber/poincare) and SimBio (github.com/hgrecco/simbio), which are Python libraries for definition and simulation of dynamical systems.   Michael Blinov  Center for Cell Analysis and Modeling, UConn Health, Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN;BioPAX;Ontologies (SBO, KiSAO);Multicellular modeling  VCell, BNGLViz, MolClustPy,   Michael Getz  PostDoc Oct 5 Oct 6 Oct 7 Oct 8 SBML;CellML;Multicellular modeling  -   Mustafa Ozen  Altos Labs Oct 7 Oct 8 SED-ML, OMEX, COMBINE;CellML;NeuroML;Multicellular modeling  -   Natasa Miskov-Zivanov  University of Pittsburgh Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN;BioPAX;SBOL, SBOL visual;CellML;NeuroML;Ontologies (SBO, KiSAO);Multicellular modeling  -   Nilesh Kumar  PhD Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;CellML  -   Norma Perez Rosas  Purdue University remotely SBML;SED-ML, OMEX, COMBINE;SBGN;Multicellular modeling  I work with mathematical models (ordinary and partial differential equations, kinetic modeling) to explain calcium activity in different biological systems.   Olga Krebs  Heidelberg Institute for Theoretical Studies HITS Oct 5 Oct 6 Oct 7 Oct 8 SED-ML, OMEX, COMBINE;SBOL, SBOL visual;Ontologies (SBO, KiSAO);BioProtocols  FAIRDOM, LiSyM Cancer, MESI-STRAT, PoLiMeR, deNBI   Paola Vera-Licona  UConn Health Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;CellML;Multicellular modeling  NETISCE (NETwork-drIven analysiS of CEllular reprogramming) http://veraliconalab.org/Netisce/index.html   Paul Jonas Jost   University of Bonn Oct 5 Oct 6 Oct 7 Oct 8 SBML;CellML;Multicellular modeling  -   Pedro Cenci Dal Castel   Indiana University Bloomington Oct 8 SBML  -   Pedro Mendes  University of Connecticut School of Medicine Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO);Multicellular modeling  -   Prashant Vaidyanathan  Oxford Biomedica remotely SBOL, SBOL visual  -   Rahuman Sheriff  European Bioinformatics Institute (EMBL-EBI) Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN;Ontologies (SBO, KiSAO);Multicellular modeling;FROG  BioModels https://www.ebi.ac.uk/biomodels   Sarah Keating  University College London remotely SBML;SED-ML, OMEX, COMBINE  -   Sebastien Moretti  SIB Swiss Institute of Bioinformatics remotely SBML;Ontologies (SBO, KiSAO)  -   Sikao Guo  PostDoc Oct 5 Oct 6 Oct 7 Oct 8 SBML;BioPAX;CellML;NeuroML;Multicellular modeling  I am currently working on developing and parallelizing NERDSS (Structure-Resolved Reaction-Diffusion Simulation Software). You can find the GitHub page at https://github.com/mjohn218/NERDSS.   Sven Sahle  Heidelberg University Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE  COPASI   T.J. Sego  University of Florida Oct 5 Oct 6 Oct 7 Oct 8 SBML;Multicellular modeling  CompuCell3D, Tissue Forge, https://directory.ufhealth.org/sego-t-j    Breakout sessions SBOL Visual Prashant Vaidyanathanm (Oxford Biomedica)\tIn these breakout sessions, we will develop into two exciting topics. First, we will explore the SBOL Visual Gallery, a novel initiative aimed at showcasing the diverse applications of SBOL visual diagrams. We will discuss strategies for encouraging the community to share their SBOL visual images and consider ways to link these images to SBOL examples. Additionally, we will brainstorm ideas for promoting these images to a wider audience through social media platforms such as Twitter and LinkedIn. Second, we will commemorate the 10th anniversary of SBOL visual by reflecting on its journey and impact over the past decade. We will discuss the evolution of SBOL visual, its contributions to the field, and its future prospects. Join us for a lively discussion on the past, present, and future of SBOL visual.\n SBOL Outreach Prashant Vaidyanathan\t(Oxford Biomedica)\tIn these breakout sessions, we will address several key topics related to the SBOL community. First, we will discuss the creation of an SBOL Projects portal or dashboard, a new effort designed to highlight tasks and ongoing projects that the community can contribute to. Second, we will explore the SBOL Release cadence, discussing strategies to ensure that the community can benefit from the latest version of SBOL. We will consider ways to keep our tools and models up-to-date to maximize the benefits for the community. Third, we will discuss outreach efforts, exploring ways to reach a wider SBOL audience, increase accessibility, and boost engagement. Lastly, we will discuss SBOL's involvement with the iGEM community and participants, brainstorming ways to enhance our collaboration and support. Join us for a productive conversation on how to strengthen the SBOL community and increase its impact.  SED2: The next generation of Simulation Experiment Design\tEran Agmon,\tLucian Smith,\tUConn Health\tIntended Audience: Researchers, bioinformaticians, software developers, and modelers keen on shaping the future of in silico experiment design standards. Familiarity with SED-ML (https://sed-ml.org/ ) is advantageous but not essential.\nOverview: The evolution of computational biology demands a more adaptable and integrative exchange format. While SED-ML has been instrumental, the emerging needs of the community call for a successor: SED2. This session will focus on the core priorities for SED2: flexibility, the ability to compose different simulation methods with custom annotations, and fostering a computational framework that works with the diverse range of simulation tools within the biological modeling community.\nSession Goals:\n SED-ML Reflection: A recap of SED-ML\u0026rsquo;s journey, emphasizing its strengths and areas of improvement. Core Priorities for SED2: Deep dive into the need for flexibility and compositionality, and the significance of custom annotations. Building a Collaborative Framework: Engage in discussions to establish a common ground where members of the Biosimulations community can converge on SED2\u0026rsquo;s direction. Exchange Format and API Exploration: Deliberate on the potential of adopting formats like JSON for SED2 and brainstorm on the design of an intuitive API for seamless interactions with the new format.   Standardizing Multicellular Simulation - Bridging Methods and Models\tEran Agmon (UConn Health),\tT.J. Sego (U of Florida); James Glazier (Indiana University)\tIntended Audience: Researchers, bioinformaticians, software developers, and modelers who are involved in or interested in multicellular simulations across various methodologies. Prior experience with basic concepts in computational biology or multicellular modeling is beneficial but not mandatory.\nOverview: Multicellular simulations have become indispensable in understanding complex biological phenomena, from tissue development to disease progression. But the diversity in simulation methods ‚ from agent-based models, cellular Potts models, cellular automata, lattice-free models, stochastic particle simulations, etc‚ poses challenges in reproducibility, modularity, reusability, and integration within multi-scale simulation. This session aims to bridge these gaps by focusing on the development of standards and schemas, with special emphasis on multiscale, embedded, and coupled simulation methods. Through a combination of presentations, case studies, and discussions, attendees will gain an understanding of the multicellular simulation landscape, the need for standardization, and the importance of sharing and reusing models.\nSession Goals:\n Landscape of Multicellular Simulations: An overview of the various methods employed in multicellular simulations, highlighting their unique features and common challenges. The Need for Standards: Discussion on the current gaps and inconsistencies in multicellular simulation methodologies and the implications for research reproducibility and collaboration. Designing Schemas for Multicellularity: Collaborative brainstorming on creating robust and flexible schemas that can cater to the diverse range of multicellular simulation methods. Integration and Interoperability: Delve into strategies for ensuring that the developed standards promote seamless integration and interoperability among different simulation tools and platforms.   FROG curation for genome-scale metabolic models Karthik Raman,\tRahuman Sheriff and other FROG contributors (Indian Institute of Technology, Madras)\nCommunity standards for consistent reconstruction, FAIR sharing and curation of constraint-based models such as genome-scale metabolic models (GEMs) are crucial to ensure their reproducibility and reliability. We initiated a community effort for a standardised assessment of reproducibility and curation of constraint-based models. Following the discussions at dedicated breakout sessions at HARMONY and COMBINE meetings over the past two years, we have developed the FROG analysis, an ensemble of analysis of constraint-based models to test the reproducibility of numerical simulation based on a set of standardized analyses. FROG analysis encompasses Flux variability analysis (FVA), Reaction deletion analysis, Objective function calculation, and Gene deletion analysis. We have also developed a collection of tools that generate FROG reports in a standardized schema to enable a reliable assessment of model reproducibility based on popular constraint-based software and a web-service. FROG analysis is currently used in BioModels‚Äô workflow to curate and build a collection of FAIR and reproducible genome-scale metabolic models.  Recent Progress and Future Work Towards Reproducible Stochastic Biological Simulation\tT.J. Sego (University of Florida); Rahuman S. Malik Sheriff (European Molecular Biology Laboratory)\tStochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology modeling, stochastic Boolean networks for network modeling, and the Cellular Potts model methodology for multicellular modeling. Proving reproducibility of simulation results is critical to establishing the credibility of a model. To this end, BioModels, the largest repository of curated mathematical models, tests and reports the reproducibility of simulation results for all submitted models when possible. A recent study showed that about 50% of the deterministic ordinary differential equation models on BioModels could not be reproduced when applying criteria for reproducibility to the information provided in their associated publication, reflecting a current crisis of reproducibility. Furthermore, there are no well-accepted metrics or standards for reproducing stochastic simulation results, thus perpetuating the crisis of reproducibility for a broad class of biological models. This breakout session aims to establish an accepted framework for testing the reproducibility of stochastic simulations in biological modeling. The session will provide an overview of recent progress towards defining quantitative measures to determine whether stochastic simulation results can be reproduced, and when results have been reproduced. Attendees will discuss current issues to address towards consensus and broad adoption in relevant modeling communities, as well as future work towards reproducibility of stochastic simulation results using multiscale and complex models.  PEtab: current state and future directions Dilan Pathirana,\tFrank Bergmann (University of Bonn)\nPEtab is a standardized file format for specifying parameter estimation problems [1]. The interoperable format is currently supported by 11 different tools [2], enabling users to benefit from standardized parameter estimation across frameworks based in Python, Julia, R, MATLAB, C++, or GUIs. Although PEtab was initially developed for parameter estimation, recent efforts have extended the format to improve standardization of various adjacent tasks, including: model selection, multi-scale modeling, PKPD and NLME modeling, optimal control, and visualization.\nIn this breakout session, based on audience interests, we will present introductions to PEtab and its extensions, then discuss current efforts to improve PEtab. People unfamiliar with PEtab are welcome to attend, and might first like to check out the tutorial [3].\n[1] \u0026ldquo;PEtab‚ Interoperable specification of parameter estimation problems in systems biology\u0026rdquo; https://doi.org/10.1371/journal.pcbi.1008646 [2] https://github.com/PEtab-dev/petab#petab-support-in-systems-biology-tools [3] https://petab.readthedocs.io/en/latest/\n Annotations for SBML-qual models\tJohn Gennari (University of Washington)\nAnnotations against standard ontological resources is an important step for model reuse, model merging, and model comprehension. What are the specific needs for annotation of \u0026ldquo;logical\u0026rdquo; models (sometimes known as Boolean models)? In this breakout session, we\u0026rsquo;ll look at some example SBML-Qual models, especially gene regulatory networks. The specific augmentations that SBML-qual provides over \u0026ldquo;plain\u0026rdquo; SBML means that there are new opportunities to provide specific types of annotations on elements. As with any annotation effort, we will discuss tool support and ways to make annotation semi-automatic or easier for the modeler. We will also discuss how in-line annotations might look within SBML-qual, versus a separate file (per the COMBINE community recommendation).\n A COMBINE Standard for Digital Twins of Living System?Rahuman Sheriff (European Bioinformatics Institute, EMBL-EBI) Digital Twins are highly accurate and dynamic virtual replicas of real-world systems that has revolutionized a wide range of engineering industry. However, as this paradigm shift extends its reach into the realm of healthcare and medicine, including the ambitious endeavour of creating a human digital twin, it becomes evident that a standardized approach is imperative.\nThe COmputational Modeling in Biology Network (COMBINE) community, renowned for its development of critical standards such as SBML, CellML, SEDML, and PETab, now faces a pivotal question: Can it deliver a standardized specification for Digital Twins of patients, encompassing the complexities of human biology and beyond?\nIn this engaging breakout session, we will explore this compelling proposition. Together, we will delve into the pressing need for a COMBINE standard tailored to the model human Digital Twins. In this session, we will engage in discussion, debating the feasibility and implications of developing a universal standard for Digital Twins that promises to shape the future of personalised medicine. If the outcome of the discussion is positive, we could consider writing a white paper on this topic.\nTutorials Biological and Biophysics Simulation in Tissue Forge: Introduction and Guided Simulation Building T.J. Sego\t(University of Florida)\nTissue Forge is open-source simulation software for interactive particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular, using a simple interface. While Tissue Forge is designed to simplify solving problems in complex subcellular, cellular and tissue biophysics, it supports applications ranging from classic molecular dynamics to agent-based multicellular systems with dynamic populations. Tissue Forge users can build and interact with models and simulations in real-time and change simulation details during execution, or execute simulations off-screen and/or remotely in high-performance computing environments. Tissue Forge provides a growing library of built-in model components along with support for user-specified models during the development and application of custom, agent-based models. Tissue Forge includes an extensive Python API for model and simulation specification via Python scripts, an IPython console and a Jupyter Notebook, as well as C and C++ APIs for integrated applications with other software tools. Tissue Forge supports installations on Windows, Linux and MacOS systems and is available for local installation via conda. This workshop introduces the basic concepts, modeling and simulation features, and some relevant modeling applications of Tissue Forge through guided simulation scripting. Workshop concepts will introduce basic Tissue Forge modeling concepts and simulation features through the development of interactive simulations in Python. Attendees are encouraged, but not required, to code along as the workshop interactively develops and tests simulations in multicellular and biophysics modeling applications.\n Bridging the Gap - A Practical Guide to Model Specification Translation in Agent-Based Modeling Juliano Ferrari Gianlupi\t(UTHSC)\nIn the world of Agent-Based Modeling (ABM), the quest for cross-platform portability and model reproducibility is a formidable challenge. This tutorial is designed to empower modelers, scientists, and researchers with the knowledge and skills to overcome this challenge using a novel Model Specification Translator.\nAgent-Based Modeling has emerged as a vital tool for exploring intricate biological systems, from cancer progression to embryonic development. However, the lack of interoperability and reusability among ABM platforms has raised concerns about model reproducibility. Our tutorial addresses these concerns head-on, introducing a practical and hands-on approach to translate models across different platforms.\nDuring this tutorial, participants will embark on a step-by-step journey through the Model Specification Translation process. We will dive into the essential concepts and methodologies necessary for seamlessly converting models from one platform to another. Whether you\u0026rsquo;re working with CompuCell3D, Tissue Forge, PhysiCell, or any other ABM platform, this tutorial will equip you with the skills needed to ensure your models remain portable and interoperable.\nAdditionally, we will showcase PhenoCellPy, a Python package that simplifies the creation of cell behavioral patterns. This tool not only enhances model accessibility for biologists but also streamlines the transition from biological concepts to computational implementation.\nParticipants should have python, a git interface (optional), and CompuCell3D (https://compucell3d.org/SrcBin ) installed. I suggest installing CC3D using conda. Please also install the xmltodict python package (https://pypi.org/project/xmltodict/ ).\nJoin us in this tutorial to explore the significance of cross-platform portability, learn how to overcome the intricacies of model porting, and contribute to the broader ABM community\u0026rsquo;s effort in establishing a universal modeling description standard. By the end of this tutorial, you will be better equipped to advance agent-based modeling, foster model reproducibility, and gain deeper insights into complex biological systems.\n Mastering Structure-Resolved Reaction-Diffusion Simulations with NERDSS Sikao Guo (Johns Hopkins University) This tutorial (https://sikaoguo22.github.io/NERDSSTutorial/ ) is intended for researchers, students, and professionals in cellular biology, biophysics, and computational biology who are interested in spatiotemporal reaction-diffusion simulation. NERDSS (https://github.com/mjohn218/NERDSS ) is a nonequilibrium reaction-diffusion self-assembly simulator that integrates molecular structures and their processes to understand the dynamics of cellular processes that last for minutes (https://doi.org/10.1016/j.bpj.2020.05.002 ). It allows users to build a reaction-diffusion model based on actual molecular structures, which enhances the model\u0026rsquo;s accuracy and captures the complexities of multisubunit complexes and their reversible formation. Several case studies have employed NERDSS, such as the formation and spontaneous disassembly of large clathrin lattices (https://doi.org/10.1371/journal.pcbi.1009969 ), the dynamic behavior of the HIV Gag lattice in virions (https://doi.org/10.7554/eLife.84881 ), and understanding the temporal influence of cofactors in retroviral Gag lattice assembly (https://doi.org/10.1016/j.bpj.2023.06.021 ). During the session, we will explore these applications, demonstrating the software\u0026rsquo;s versatility in handling diverse cellular processes. The session will cover core principles of structure-resolved reaction-diffusion, emphasizing its role in cellular biology. We will attempt to build a coarse-grained structure from the real protein structure from the pdb database. Then, we will learn how to set up a model, run the model with NERDSS, analyze and visualize the model outcomes with io_nerdss (https://github.com/mjohn218/io_nerdss ) and OVITO.\n Tutorial on biological modeling with PySB Mustafa Ozen\tRyan Spangler, Carlos F. Lopez\t(Altos Labs) PySB (Python Systems Biology) is a powerful and versatile biological modeling tool that has gained prominence in systems biology. It provides a Python-based programming platform with a rule-based framework for constructing dynamic models of sophisticated biochemical systems, enabling researchers to simulate and analyze complex cellular processes. This unique tool empowers researchers to modularly define molecular interactions and transformations, facilitating the representation of a wide array of biological processes in a simple, interpretable way. PySB accommodates both stochastic and deterministic simulation methods, providing a comprehensive view of system behavior. Its seamless integration with various model calibration, analysis, and visualization libraries further assists researchers in interpreting simulation results effectively. In this tutorial session, we aim to walk the attendants through the foundations of PySB, show them how it works, and provide them with hands-on experience.\nRelevant Resources: PySB Paper: https://identifiers.org/doi/10.1038/msb.2013.1 PySB Website: https://pysb.org/ PySB GitHub: https://github.com/pysb/pysb PySB Tutorial: https://pysb.readthedocs.io/en/stable/tutorial.html\n Introducing poincaré and SimBio Mauro Silberberg (Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisica)\tPoincaré is a new Python-based library to define and simulate dynamical systems. Trying not to reinvent (much of) the wheel, it uses modern Python syntax to define and compose models in a compact way. This allows us to take advantage of the huge investment on tooling from the broader Python community such as static type checkers, code linters and formatters, autocomplete and refactoring features from IDEs, among others. Using standard libraries from the PyData ecosystem, by default, poincare compiles into a first-order ODE system using NumPy arrays, and uses solvers from SciPy. But it also provides different backends such as Numba, which compiles just-in-time to LLVM code, providing a significant speed boost, or JAX, which provides autodifferentiation tools targeted for ML. Additionally, it supports units using the Pint library.\nSimBio is built on top of poincaré, adding some components for reaction-based models used in systems biology. It provides some predefined building blocks for the most common reactions, but allows easily to create your own. Finally, it implements an importer and exporter to SBML, allowing to interexchange models with the COMBINE community. We hope that it is simple enough for beginners, but powerful for power-users with the possibility to extend and compose with the large Python ecosystem.\n DySE: Dynamic System Explanation framework Difei Tang (University of Pittsbrugh); Natasa Miskov-Zivanov (University of Pittsburgh)\nIn this demo, we will showcase our framework, DySE (Dynamic System Explanation), that includes tools for model simulation, model extension, interaction classification, interaction filtering, model checking, and sensitivity analysis. The rapid proliferation of data generated by experiments studying biological systems poses a considerable challenge. This overflow of information is spread across an array of publishing platforms, making it increasingly difficult to manually analyze all available data. This underscores the necessity for automated methods that can retrieve and connect relevant pieces of this voluminous knowledge. Such methods are crucial for understanding, explaining, and predicting the behavior of these complex systems.\nTo tackle this challenge, DySE integrates machine reading, automated model assembly, and computational analysis to enhance understanding and explanation of complex systems. The toolset is conveniently accessible via a user-friendly graphical interface (GUI).\nFLUTE utilizes existing databases to evaluate confidence and trustworthiness of given biochemical interactions (https://melody-flute.readthedocs.io/en/latest/ ). VIOLIN classifies large sets of interactions with respect to a given model. The interactions are classified into four main categories, corroborations, contradictions, extensions, and flagged, and several subcategories within main ones (https://github.com/pitt-miskov-zivanov-lab/violin). CLARINET (see https://github.com/pitt-miskov-zivanov-lab/clarinet and link to binder notebook on main page) and ACCORDION (see https://github.com/pitt-miskov-zivanov-lab/accordion and link to binder notebook on main page) automatically expand and recommend models based on selected desired model properties.\nIn conjunction with these front-end tools, we\u0026rsquo;ve also developed back-end tools within the DySE framework. DiSH is a stochastic simulator offering versatile simulation schemes and timing options (https://tinyurl.com/dishjupyter). PIANO provides comprehensive sensitivity analysis for the entire model, and allows for identifying most influential pathways and suggesting interventions (https://github.com/pitt-miskov-zivanov-lab/dyse_wm/blob/main/examples/sa_test_hybrid.ipynb ). Additionally, we\u0026rsquo;ve introduced a unified format compatible with the tools mentioned above: BioRECIPE (https://melody-biorecipe.readthedocs.io/en/latest/ ), seamlessly translating to and from widely used synthetic biology modeling languages.\nAll of these tools can be used either independently or in combination. For instance, synthetic biologists can rely on it to ensure the reliability of interactions in designing synthetic biological systems. Bioinformaticians can efficiently filter and prioritize data, while computational modelers benefit from model extensions to always get model up-to-date. Professionals in biotech industries utilize sensitivity analysis for optimizing therapies. Additionally, even educators would find it valuable when using simulation software.\n  Novel advances in the automation of knowledge selection and model assembly Natasa Miskov-Zivanov, Yasmine Ahmed, Gaoxiang Zhou\t(University of Pittsburgh)\nCreating computational models of complicated systems, including intracellular and intercellular bionetworks, is a time and labor-intensive task which is often limited by the knowledge and experience of Pathway database modelers. This has naturally led to the emergence of the idea of automating the process of building new/extending existing models, which could have a significant potential in enabling rapid, consistent, comprehensive and robust analysis of complicated systems. Inspired by this idea, we propose in this work different novel approaches namely ACCORDION (ACCelerating and Optimizing model RecommenDatIONs) and CLARINET (CLARifying NETworks) for expanding models using the information extracted from literature by machine reading engines. Our proposed approaches combine machine reading with clustering, and graph theoretical analysis to create an automated framework for efficient model assembly. Furthermore, by automatically extending models with the information published in literature, our proposed methods allow for collecting the existing information in a consistent and comprehensive way. This, in turn, facilitates information reuse, data reproducibility, and replacing hundreds/thousands of manual experiments, thereby reducing the time needed for the advancement of knowledge. To evaluate ACCORDION1 and CLARINET, we compare their outcomes with three previously published manually created models namely naive T cell differentiation model, T cell large granular lymphocyte leukemia model and pancreatic cancer cell model. Besides demonstrating automated reconstruction of a model that was previously built manually, our tools can assemble multiple models that satisfy desired system properties. As such, they replace large number of tedious or even impractical manual experiments and guide alternative hypotheses and interventions in biological systems. A GitHub page, ReadtheDocs and Jupyter notebook are available for ACCORDION https://github.com/pitt-miskov-zivanov-lab/accordion and CLARINET https://github.com/pitt-miskov-zivanov-lab/clarinet.\n Using Compucell3D as a Platform for Model Building to Explore Cell Behaviors, Cell-Cell Interactions, Cell Migration and Chemotaxis  Pedro Dal-Castel (Biocomplexity Institute and Department of Intelligent Systems Engineering, Indiana University)\nMechanistic agent-based modeling is an integral part of contemporary bioscience, used for hypothesis generation and testing, experiment design and interpretation, and the design of therapeutic interventions. The CompuCell3D (CC3D) modeling environment allows researchers to rapidly build and execute complex virtual tissue simulations with minimal programming experience. CC3D enables biological simulations from subcellular to tissue scales, supporting explicit cell shapes, cell migration, contact-mediated cell interactions, soluble signals, and complex cell state dynamics (gene regulatory, signaling, and metabolic networks). CC3D natively supports SBML, Antimony, and MaBoSS network model integration. Participants will (1) learn how to build models in CC3D, (2) implement network models in CC3D, and (3) develop an example simulation with all concepts learned. CC3D can be accessed from the official website (www.compucell3d.org) or running it on-line at (https://nanohub.org/tools/cc3dbase4x ).\nAudience: Anyone interested in multicellular Virtual-Tissue modeling or in coupling network models to cell behaviors and dynamic spatial organization. If you plan on participating, please fill out this form: https://forms.gle/TTnw88hR3PebCkmE7\nLearning Outcomes: Ability to use CompuCell3D to design, execute and explore virtual-tissue simulations integrating cells, networks and external chemical fields.\nComputer Requirements: Any Windows or Mac computer. CompuCell3D is open-source and free. It also runs on many LINUX deployments (see www.compucell3d.org for details). Our preferred method for this miniworkshop is launching CC3D from nanoHUB. We ask that you open an account in advance (https://nanohub.org/register/ ).\nClass materials: https://drive.google.com/drive/folders/1RJMgfO9PDGvpfJ5Fp7OvVouNK9DvDuW5?usp=drive_link Zoom session https://iu.zoom.us/j/4555920347 For more information, see https://www.compucell3d.org or contact pdalcastel@gmail.com, or jaglazier@gmail.com\n  Talks Multicellular and Multiscale Models of Microbes and Host Systems Elebeoba May (U Wisconsin-Madison) Computational and experimental models enable concurrent spatiotemporal and biochemical modeling, monitoring and characterization of microbe-microbe and microbe-host interactions to understand bacterial communities and infection dynamics and outcome. We have developed multiple in silico intracellular and multicellular models to probe the contribution of physiological, structural and biochemical processes in control, resolution or dissemination of bacteria in models of bacterial communities and mycobacterium infection. In this talk, we will highlight multiscale models including models of Mycobacterium tuberculosis (Mtb), an intracellular pathogen, that can adapt to changing environments within host phagocytic cells enabling persistence and proliferation during infection and onset of disease. Our models integrate host and pathogen interactions using a multiscale, agent-based models (ABM). Models are informed by empirical characterization studies and account for changes in the physiological environment of the host as well as the host intracellular environment. We discuss expanded models and challenges in developing models to explore response in individuals with chronic obstructive pulmonary disease (COPD) and tuberculosis.\n Multi-Scale Multicellular Agent-Based Virtual-Tissue Simulations: Challenges and Opportunities in Sharable Model Specification James Glazier (Indiana University) Multi-scale, Multicellular Agent-Based Virtual-Tissue models built using modeling frameworks like CompuCell3D are versatile tools for exploring the complex interactions between signaling and gene- regulatory networks, icell-cell signaling through contact and diffusible signals, and force generation, cell migration, proliferation and shape change, and finally for coupling to much higher scales such as the whole body, the environment and populations. They can play a crucial role in helping to interpret and design more informative experiments, such as in vitro to in vivo extrapolation. However, Virtual Tissues currently lack model-specification standards, support for modular architectures and annotation, cross-compatible tools for model specification, visualization and analysis, and a model sharing infrastructure. This last aspect of a model sharing infrastructure has enabled the rapid development of systems biology network modeling as a core technology in research and is gaining wider acceptance in regulatory environments. Comparable infrastructure is essential for Virtual Tissues to move from academic one-offs for basic research to mainstream technologies in biomedicine, technology and regulation. Because Virtual Tissues are substantially more complex and structurally and functionally more diverse than network models, standardization and modularization, graphical specification and distribution are all more challenging. I will consider some of the variety of Virtual Tissue applications, frameworks and modeling approaches and some of the challenges and opportunities we face in developing an effective ecosystem of tools and standards.\n Breaking Barriers in Multiscale Agent-Based Models: A Path for Cross-Platform Models Juliano Ferrari Gianlupi (UTHSC) Agent-based modeling (ABM) is a powerful tool for understanding complex biological systems such as cancer progression, embryonic development, and pathogen infections. Ensuring reliable and accurate simulations is crucial as ABMs gain prominence. This research focuses on addressing the crisis of reproducibility in ABMs through two approaches. First, we introduce a model specification translator to facilitate cross-platform model reproducibility. Second, we present PhenoCellPy, a cross-platform Python package that simplifies the creation of cell behavioral patterns, making modeling more accessible to biologists and improving inter-platform operability. Biological systems often exhibit stereotyped transitions between distinct phases, necessitating structured definitions of states and transitions. Translating cellular behaviors into computational models requires a deep understanding of both biology and modeling. To enhance model sharing and accessibility we created PhenoCellPy. We aim to create pattern specifications usable across various modeling platforms, streamlining the transition from biological concepts to computational implementation, as patterns would have to be recreated for each new model. The need for cross-platform portability and interoperability is critical for model validation. While challenges exist in achieving model portability, we emphasize the importance of establishing a universal modeling description standard akin to SBML, calling for a collaborative effort within the AB modeling community. We investigate some of the challenges this universal ABM specification will face, and make headway into its creation with our model specification translator. It can translate PhysiCell models into CompuCell3D models.  MolClustPy: a Python package to characterize multivalent biomolecular clusters Aniruddha Chattaraj (Harvard U) Low-affinity interactions among multivalent biomolecules may lead to the formation of molecular complexes that undergo phase transitions to become supply-limited large clusters. In stochastic simulations, such clusters display a wide range of sizes and compositions. We have developed a Python package, MolClustPy, which performs multiple stochastic simulation runs using NFsim (Network-Free stochastic simulator); MolClustPy characterizes and visualizes the distribution of cluster sizes, molecular composition, and bonds across molecular clusters. The statistical analysis offered by MolClustPy is readily applicable to other stochastic simulation software, such as SpringSaLaD and ReaDDy.  FAIRDOM-SEEK: FAIR and standartised management of models and related (meta)data. Olga Krebs (Heidelberg Institute for Theoretical Studies, Germany) FAIRDOM-SEEK (https://fairdomseek.org/ ) is an open source software for storing, cataloguing, sharing and reusing research outcomes, it is designed to support the principles of FAIR (Findable, Accessible, Interoperable, and Reusable) research data management. FAIRDOM-SEEK offers features that enable scientists to organize, document, and publish their research data. The ISA (Investigation, Study, Assay) standard framework supports the organization and description of individual experiments and related research items, such standard operating procedures, or protocols. Key components of FAIRDOM-SEEK include data and metadata management, version control of files, and integration with modelling tools, e.g. JWS online and Copasi. Additionally, FAIRDOM-SEEK promotes collaboration by providing mechanisms for sharing and exchanging metadata and research outputs with specific individuals, research groups, and the public. The possibility to create persistent identifiers (DOI) for public data files or experiments allows for long term access to research outputs that can be used as e.g. supplementary material in publications. The SEEK platform enables the building of Project Hubs where investigators can store, share, access, connect and interact with digital objects generated from their research, and use them in their own analyses. FAIRDOMHub is used as a research data management platform by 350 national and international collaborative projects not only as a data repository but also as a knowledge-sharing platform. It encourages the creation of communities and fosters interdisciplinary collaborations by connecting researchers with shared interests and expertise. FAIRDOMHub is developed and maintained by the FAIRDOM (https://fair- dom.org/ ) consortium and is a key component of the data management services of de.NBI, the German Network for Bioinformatics Infrastructure (https://www.denbi.de/ ), and ELIXIR, the European Infrastructure for Life Sciences (https://elixir-europe.org/ ).  Simulation-Driven Evaluation of Genetic Circuit Architectures Using Combinatorial Designs with the Synthetic Biology Open Language (SBOL) Helen Scott (Raytheon BBN) The field of synthetic biology has advanced by developing “parts”, genetic elements and tools with defined functions, and then combining these parts to create circuits with increasing complexity. As DNA synthesis technology and assembly methods have improved, synthetic biologists are now able to combine these parts into more complex circuits with more advanced functions. However, when designing a circuit, fully exploring the combinatorial space of relevant parts can be time and cost prohibitive to carry out in the lab. One possible way to exhaustively search this combinatorial space is to construct a SBOL generator for each modular element of the genetic circuit. These elements can then be assembled combinatorically to generate a genetic regulatory network for each possible configuration. An SBOL representation of these circuits can then aide in simulation-based engineering, as LaTeX equations and MATLAB code can be generated programmatically for each such genetic regulatory network. Here we present two uses of combinatorial design with SBOL for the comparative evaluation of potential genetic circuit architectures and their sensitivity to parameter values: the first modularly combined regulatory elements to investigate time- delayed safety switches for CRISPR gene therapies, and the second combined CRISPRi-gRNA target sites to investigate architectures for synthetic plant promoters. We anticipate that by aiding in combinatorial design, SBOL can allow for faster engineering of genetic circuits across many applications. This work was supported by DARPA contract HR0011-18-2-0049. This document does not contain technology or technical data controlled under either U.S. International Traffic in Arms Regulation or U.S. Export Administration Regulations. Views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. Approved for public release, distribution unlimited (DISTAR Case 38663).  Knowledge-Based Pathway Extraction and Validation in Cell Signaling Networks Gaoxiang Zhou (UPitt) In system biology, achieving precise control in cell signaling networks is paramount, and pathway analysis is a vital tool in this endeavor. It helps identify key genes, enzymes, and reactions within pathways, offering insights into their interactions and behaviors. Nonetheless, current approaches primarily centered on establishing connections between isolated interactions of two spices frequently fall short in providing the essential biological context required for precise analysis. To tackle this issue, this study introduces a knowledge-based (KB) pathway extraction method and develops a hands-on python-based toolkit. By incorporating this approach and a rigorous validation scheme, system biologists gain a powerful method for precise pathway analysis. The methodology underlying this approach entails the assignment of scores to pathways and extraction based on path scores for certain source-target node pairs. Subsequently, a validation scheme is introduced to validate the extraction results. This scheme is designed to preserve the biological properties. Specifically, it aims to demonstrate that the removal of crucial pathways, achieved computationally through regulatory knockdown, should have an impact on these properties, while the removal of less significant pathways should not. To achieve this, a set of properties inherent to the original modeled system is established based on expert knowledge. Partial models are then created by eliminating the highest-ranked pathways. The evaluation of these partial models against the defined properties is conducted using a combination of statistical model checking and element-based simulations. The core of the methodology lies in the graph search algorithm, which identifies the most \"important\" paths in a weighted directed graph from a source to a target. Different interpretations of importance lead to diverse edge weight assignments. Nine attributes are proposed for weight assignment in this work, including in-degree, out-degree, shortest link, loop count, non-bias, immediate edge influence, and element sensitivity. Each attribute offers a unique perspective on pathway importance. They are elaborately compared and contrasted in the context of a case study. Our case study centers on a T-cell differentiation model, wherein we investigate various scenarios and evaluate the consequences of pathway removal based on diverse interpretations of significance. The findings illustrate that, in most scenarios, the model's behavior is most significantly affected when pathways are removed based on immediate edge influence and element sensitivity attributes. Immediate edge influence and element sensitivity are conceptualized to capture aspects of network topology, dynamics, and, notably, knowledge semantics. These outcomes underscore the critical role of knowledge-based pathway analysis in the study of biological behaviors.   Lightning talks The Reproducibility Portal Herbert Sauro, Lucian Smith, Joe Hellerstein (U Washington) Reproducibility is a foundation of science. In Systems Biology, this requires access to details of models and modeling results. Much of this information exists in websites such as BioModels and Biosimulations, but accessing the information can be complicated. The Reproducibility Portal (https://www.reproducibilityportal.org/ ) provides simple and fast access to information such as: the article summary, human-readable rendering of SBML models, and the ability to explore simulation runs. The Portal is a website hosted as a GitHub page.\n  Constrained Fitting of Rule-based Models with Simmune Fengkai Zhang (NIH)  Rule-based modeling approaches allow modelers to construct molecular interaction networks based on the specification of ‘rules’ for bi-molecular interactions and molecular complex state transitions. These rules can encompass details such as, for example, sub-molecular interaction domains and the phosphorylation and binding states of the involved molecules. The modeling platform Simmune uses rule-based encoding to simulate models of cellular signaling pathways in well-stirred systems or realistic geometries. The software also offers tools for detailed analyses of simulation results and novel strategies for fitting model parameters using user-defined constraints on the values for model observables. We will demonstrate the capabilities of these modeling strategies using cytokine signaling network models. This work is supported by the intramural program of the NIAID, NIH.   Antimony at 15 Lucian Smith (U Washington)\nAntimony is a human-readable, human-writeable model format, adapted from Jarnac in 2008 that can be translated to and from SBML. This has formed a lynchpin of our Tellurium system, enabling modelers to easily create models. Here, I cover more recent updates to the language and particularly the challenges of trying to easily annotate models.   SBML tools and browser based modelingb Bartholomew Jardine (U Washington) REMOTE Browser based, client-side applications are increasing in popularity as they have certain advantages over traditional native code and server-side applications. As they are browser based the user does not need to install it, just click the link and the application loads, and current browser javascript interpreters are highly optimized and execute javascript and web assembly at near native application speed. As a client-side application, the code is run on the user’s computer with no server-side needs which enables ‘dumb’ websites to host the application as the site is basically used as a file server. For the SBML (sbml.org) community we have two libraries: libsbmljs (https://github.com/sys-bio/libsbmljs ) and libantimonyjs (https://github.com/sys-bio/libantimonyjs ) and a couple of implementations: MakeSBML (https://sys-bio.github.io/makesbml/ ), an application that makes converting SBML models to Antimony easy and miniSidewinder (https://github.com/sys-bio/miniSidewinder ), a lightweight simulator of SBML models, that use the libantimonyjs and libsbmljs libraries and show what is possible in browser based modeling and simulation.   Retroactive Curation: Lessons and Challenges Lucian Smith (U Washington)\nSince 2005, curators at the EBI (European Bioinformatics Institute) have been curating papers, creating SBML models that can be used to reproduce figures in papers. With the advent of SED-ML (the Simulation Experiment Description Markup Language), it became possible to not only encode the model used to produce the figures, but also to encode how to create the figure from the model. At the Center for Reproducible Biomedical Modeling, we have been working on re-curating Biomodels to add SED-ML files, and run the resulting OMEX files at biosimulations.org on multiple simulators to confirm validity. To date, 829 SED-ML files run and produce the same results on multiple simulators, and 1035 SED- ML files run on at least one simulator.   ENSEMBLE MODELING OF BACTERIAL RESPONSE TO IRON AND OXIDATIVE STRESS Daniel Ajuzie (U Houston) BACKGROUND: Iron regulation in bacteria is complex and influenced by environmental factors such as oxidants [1]. Models exist for cellular iron regulation and oxidative stress response, but few address the challenge of modeling multiple phenotypes. Our previous in-silico model integrated iron and hydrogen peroxide stress response in Escherichia coli K12. Here, we present a multi-phenotype approach for parametrizing the iron stress response model, to improve prediction accuracy across multiple phenotypes. METHODS: Experimental models have demonstrated that Escherichia coli (E. coli) can exhibit different phenotypes, including proliferative, bacteriostatic, or bactericidal, depending on the combination and intensity of stress factors. We integrated and expanded on previous models to construct a two compartmental model of that captures iron[2] and oxidative stress[3] interactions and resolves response in E. coli to varying concentrations of ferric iron, ferrous iron and hydrogen peroxide stress at different scales of genetic regulation, metabolic response and physiological response. We employed augmented sensitivity analysis [4] to identify influential parameters for our model and utilized multi-phenotype assumption (MP) and sequential parameter estimation in the optimization approach. Ensemble modeling methods were used to aggregate single models to improve prediction accuracy. To validate our model, we compared its ability to replicate the same response to stress conditions as the experiments. Additionally, we compared our MP approach with standard single phenotype (SP) approaches. RESULTS: The MP model accurately recapitulated 70 - 80% of experimental response variables across 20 distinct stress-response categories compared to 65 – 75% obtained using SP approaches. Ensemble modeling was found to reduce modeling error by up to 11% across the different categories for both the MP and SP models. Using the MP model, we identified siderophore production, growth, and peroxide-dependent transcriptional regulation as the most critical sub-components of the iron homeostatic machinery in E. coli necessary for developing an adequate predictive model. Additionally, our models explained bacterial siderophore response in the context of dynamic iron and peroxide stress. Results seem to suggest that enterobactin is causally correlated with cellular growth parameters and likely confers cellular protection under peroxide stress independent of iron stress. Our model simulations uncover that low levels of peroxide stress in an iron-rich environment pose a challenging scenario for bacterial adaptation, resulting in a bacteriostatic phenotype. This difficulty can be attributed to the intricate interplay between genetic regulation and metabolic response under this specific combination and intensity of stress. CONCLUSIONS: Understanding variations in bacterial persistence resulting from differences in the maintenance of iron homeostatic processes could aid in the identification of potential therapeutic targets or novel therapeutic strategies for host-pathogen dynamics. An immediate future application for this model would be its integration into multiscale model of biofilm formation [5] developed in our laboratory to understand how iron metabolism and oxidative stress impacts processes involved in biofilm formation.  Curating models from Biomodels: Developing a workflow for creating OMEX files Jin Xu (U Washington) I examined a selection of models in the Biomodels Database. For each model, I reproduced the published results using Tellurium. Once reproduced I manually created a standard OMEX file using SBML and SEDML. These exercises have allowed me to develop a workflow that we will use to develop an online platform to help users more easily curate models for biosimulations.org and www.reproducibilityportal.org.\n Introducing the BioRECIPE Format: A Human-Centric Representation For Computational Modeling in Systems Biology Gaoxiang Zhou, Difei Tang, Natasa Miskov-Zivanov (U Pitt) In the field of systems biology, widely employed representation formats for computational modeling, such as SBML, CellML, and BioPAX, typically rely on markup languages and prioritize computer-friendliness. However, these formats often lack accessibility for human modelers and experts when it comes to the tasks of model creation, verification, evaluation, curation, and expansion. There is a growing demand for a format that enables human users to intuitively preview and modify various aspects of models, including individual model elements, interactions between these elements, and even the attributes associated with these interactions. In this study, we introduce the BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) format to address this demand. BioRECIPE is primarily a tabular format, ideally suited for models structured as directed graphs, while retaining machine-readability and compatibility with a range of model development and analysis tools. The BioRECIPE format serves a dual purpose, allowing the representation of two distinct formats: event-based lists of interactions and element-based models. In the event-based format, each row corresponds to a single interaction, with column headers aligning with interaction attribute names, categorizing attributes into elements, interactions, context, and provenance. On the other hand, the element-based model format assigns each row to a model element and supports the representation of a model\u0026rsquo;s static graph structure along with attributes necessary for dynamic analysis. Unlike the event-based format, multiple interactions can be combined within element update rules. This format accommodates various model representation schemes, ranging from less to more detailed, including static and dynamic parameters. Additionally, this format incorporates three attribute groups for defining rules concerning element state changes, namely element regulation, value, and timing. The BioRECIPE format is presently compatible with established representation formats like SBML and JSON, facilitating seamless translation between various output formats obtained from REACH, TRIPS, and INDRA. Furthermore, it serves as a standardized format within the DySE framework and is integrated into many analysis tools inside, including FLUTE, VIOLIN, CLARINET, ACCORDION, FIDDLE, and PIANO. The detailed documentation of this BioRECIPE format can be accessed at https://melody-biorecipe.readthedocs.io/\n  Alcuin: A cross-platform Qt/C++ portable library to create an embeddable widget with customizable features required for a network viewer/editor software tool. Adel Heydarabadipour \u0026amp; Herbert M. Sauro. (U Washington) REMOTE Alcuin is an open-source cross-platform Qt/C++ portable library that provides developers with an embeddable widget with the required features for a network viewer/editor software tool. With minimal effort, a developer can embed this widget into their own software tool and provide their users with a user interface to view, build, and edit a network consisting of nodes and edges. Alcuin is shipped with the fundamental features of a network viewer/editor tool, including adding/removing nodes to its graphics scene, adding/removing edges (with optional arrowheads) between nodes, nesting one node into another node, modifying the properties of network elements (nodes, edges, and arrowheads), selecting, moving, copying, cutting, pasting, aligning, dragging and dropping network elements, zooming and panning on its graphics scene, and undoing and redoing the user’s actions. In addition, Alcuin is equipped with a plugin interface that lets developers use python scripts to customize it at their will to meet the specific requirements of their users. As a use case, we show how its plugin interface can be implemented to customize this widget into a tool for viewing, building, and editing biochemical reaction networks formatted using SBML. Using this customized tool, a user can create, load, save or edit biochemical reaction networks compatible with SBML as well as the SBML Layout and Render. The name Alcuin refers to the 8th century English scholar and teacher who was headmaster in 778 AD at the cathedral school of York, England and later became master of the palace school of Charlemagne at Aachen in 782 AD. The source code of the project along with its binary installers for Windows and macOS platforms are available on its GitHub page, https://github.com/adelhpour/NetworkEditorGUI.\n  Posters  cOmicsArt - customisable Omics analysis reporting tool Paul Jonas Jost (U Bonn) Modern researchers often face a daunting challenge when dealing with the vast amounts of data generated by omics technologies. Navigating this data typically demands either a proficiency in programming or the need to seek assistance, both of which can impose constraints on the research exploration process. To address this issue, we introduce a web-based software tool developed in R. This tool serves as an installation-free graphical user interface, designed to offer an interactive and accessible means for initial data exploration. Upon uploading the data matrix and sample names, the platform offers a wide array of data-selection options, diverse preprocessing techniques, and essential preliminary analyses with interactive features. These include Principal Component Analyses (PCAs), Volcano Plots, heatmaps, basic differential expression analysis as well as enrichment analysis. A key feature ensuring research reproducibility is the automatic generation of a detailed exploration report. Every alteration made to the raw data is meticulously documented. Additionally, any plots that users choose to save are seamlessly integrated into the report, complete with their corresponding settings. Moreover, for those interested in further manipulating the plots, an R code can be readily downloaded. This code empowers users to reproduce and customize the plots directly within the R environment. Alternatively, the plots can be effortlessly downloaded in various image formats. This tool democratizes the data exploration process, making it accessible to researchers regardless of their programming background. Researchers can now explore and experiment with their omics data, undertaking crucial initial steps in their analysis independently. The tool is designed to empower experimentalists to engage with their data according to their specific interests, thereby reducing the burden associated with subsequent analysis.\n  Metadata Management: A Synchronous Metadata Recording Approach Lea Seep (UBonn) In scientific collaboration metadata management is critical for data reproducibility. However, wet-lab researchers need to patch together diverse set of metadata standards for the different stages during the data lifecycle. Consequently, metadata is frequently gathered retrospective at point of publication, which can miss pre-publication collaboration and knowledge sharing opportunities. Our introduced metadata structure aligns with the data lifecycle for synchronous metadata recording, covering the planning to data collection for an experimental design and measurement combination. Its implementation within Excel offers several features to streamline the recording process, including automatic structure selection, metadata integrity checks and export options for various formats required by repositories. The design prioritizes the ease of complete data recording over structural robustness. We anticipate the deployment of centralized database for metadata records by providing a suitable ontology. The proposed metadata structure simplifies recording and structuring for wet-lab scientists, promoting practicality, and convenience in metadata management. This framework can accelerate scientific progress by enhancing collaboration and knowledge transfer throughout intermediate steps of data creation.  pyPESTO: PYthon Parameter EStimation Toolbox Maren Philipps (U Bonn) pyPESTO is a widely applicable and highly customizable toolbox for parameter estimation. It can be used as a parameter estimation pipeline for systems biology problems specified in SBML and PEtab. The interface to AMICI enables efficient simulation and sensitivity analysis of ordinary differential equation (ODE) models. Toolbox features include multi-start local optimization, profile computation and visualization. Notably, it accommodates parameter estimation with ordinal data, censored data and nonlinear-monotone data.   Model selection with PETAB Dilan Pathirana (U Bonn) Model selection is the task of identifying useful models from a set of plausible models. Often, this involves calibration of models, then subsequent comparison of models by some criterion, e.g. the Akaike (AIC) or Bayesian information criterion (BIC). PEtab itself is a file format to specify the parameter estimation problem for a model, including the objective function noise model and data, which facilitates calibration of single models. We extend PEtab to support model selection (PEtab Select), by (1) designing a concise file format for the specification of models and hyperparameters, and (2) creating a software library for model selection algorithms. This software library enables tools that already support the PEtab format, to easily add model selection capabilities, by simply interfacing the PEtab Select library. PEtab Select is currently supported by some popular systems biology tools, including COPASI, PEtab.jl, and pyPESTO. Implemented algorithms include stepwise methods like forward and backward, and well as brute- force and the state-of-the-art stepwise method FAMoS. PEtab Select has been used to solve large model selection problems from the literature, including a synthetic-data problem with 65,000 models, and a real- data problem with 4 billion models.  Time-dependent parameters and optimal control with PEtab Dilan Pathirana (U Bonn) Models in systems biology can involve time-dependent parameters. These can be used to encode evolving governmental interventions strategies during a pandemic, or adjustable patient-specific drug regimens. The values that these parameters take over the timecourse are typically considered independent of the mathematical model that describes the dynamics of the system. Hence, keeping them separate from the model can help make patient-specific models more modular. PEtab is a file format to specify the parameter estimation problem for a model, such that the model can be calibrated. We extend PEtab to support complex experimental conditions involving time-dependent parameters (PEtab Timecourse). We further extend this to support optimal control of these time-dependent parameters (PEtab Control). In both extensions, we (1) introduce new file formats to concisely specify the new information and (2) provide software libraries that enable SBML- or PEtab-compatible tools to solve these extended problems, by converting the extended problems to standard SBML and PEtab. We demonstrate these extensions in a real application example of patients in an ICU setting, where they are treated with time-dependent doses of glucose and insulin to achieve healthy blood glucose levels. The optimal control problem is to identify drug doses that keep the patient healthy. Here, one key challenge is that this is an online setting, where new patient data arrives every 15 minutes, and a new drug dose regimen should be proposed on a similar timescale. ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"f9b46192ca344c9e54e8e9d9dc28342c","permalink":"/author/combine-2023/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2023/","section":"authors","summary":"NEWS October 4:\n 78 attendees 9 breakouts, 8 tutorials, 8 talks, 11 lightning talks, and posters.  The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields.","tags":null,"title":"COMBINE 2023","type":"authors"},{"authors":null,"categories":null,"content":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2024 will be a workshop-style event hosted at the University of Stuttgart in Stuttgart, Germany with support of the German Research Foundation (DFG) through the International scientific events program, the Stuttgart Center for Simulation Science (SimTech) and the Stuttgart Research Center Systems Biology (SRCSB). The meeting will be held in September 2024, closely aligned with the dates of the Virtual Physiological Human (VPH)2024 Conference September 04-06 Stuttgart, Germany.\nThe official programm takes place from Sunday 01st to Tuesday 3rd September. On Wednesday 4th and Thursday 5th September, there will be rooms provided for personal meetings only. The meeting days will include talks about the COMBINE standards and associated or related standardization efforts, presentations of tools using these standards, breakout sessions for detailed discussions as well as tutorials. There will be also a dedicated poster session, participants are encouraged to bring posters - poster boards will be provided next to meeting places. Some time each day will be left for community discussion and wrap-ups of breakouts and advertisements for following breakouts. It will be primarily an in-person meeting, with individual breakout sessions responsible for enabling remote participation as needed.\nLocal organizers are Nicole Radde (nicole.radde@simtech.uni-stuttgart.de) and Sebastian Höpfl (sebastian.hoepfl@isa.uni-stuttgart.de).\nConfirmed Keynote Speakers and Session Chairs  Irina Balaur, University of Luxembourg, Luxembourg Dirk Drasdo, Director of Research INRIA (French National Institut(ion) for Research in Computer Science and Control), Rocquencourt, France Fabian Fröhlich, Francis Crick Institute, United Kingdom Marc-Thorsten Hütt, Constructor University Bremen, Germany Matthias König, Humboldt-University Berlin, Germany Heinz Köppl, TU Darmstadt, Germany Göksel Misirli, Keele University, United Kingdom David Nickerson, Auckland Bioengineering Institute, University of Auckland, New Zealand Herbert Sauro, University of Washington, USA Lucian Smith, University of Washington, USA Judith Wodke, University Medicine Greifswald, Germany  Funded by and A tentative schedule Note that many events are scheduled somewhat spontaneously at these events; keep an eye out here or on the COMBINE slack for last-minute changes and additions.\nWorkshop Location COMBINE 2024 takes place at the University of Stuttgart in Stuttgart, Germany. COMBINE 2024 will take place in the former Campus Guest building, at Universitätsstrasse 34, 70569 Stuttgart. If you do not find the venue, email sebastian.hoepfl@isa.uni-stuttgart.de or nicole.radde@simtech.uni-stuttgart.de, or ping us on the COMBINE slack channel.\nArrival and Transportation The closest airport is the Stuttgart Airport (STR). However, overseas the International Airport of Frankfurt Frankfurt Airport (FRA) is probably the better choice. There are ICEs and ICs going from the Frankfurt Airport to Stuttgart every one to two hours. You can book the train tickets via the Deutsche Bahn website. The Campus in Stuttgart, where we will host the Combine2024 is a 10 minute drive from the city center of Stuttgart. Unfortunately, the main line of the Sbahn is still closed during the COMBINE period. There is a rail replacement service (SEV) that serves all stops every 5 minutes Replacement Service. You can take any of these buses to the Universität stop when arriving at Stuttgart Central Station. If you arrive at Stuttgart airport, take the S-Bahn S2 to „Schorndorf“ or S3 to „Backnang“. In this case you can change to the bus replacement service (SEV) at the train station \u0026ldquo;Stuttgart Vaihingen\u0026rdquo;. Alternatively, if you come by car, set your destination at \u0026ldquo;Universitätsstrasse 34. 70569 Stuttgart (Campus Vaihingen)\u0026rdquo;.\nAccomodation There are no hotels at the workshop venue. However, you can find accommodations along the S-Bahn route, such as near the stations \u0026ldquo;Hauptbahnhof\u0026rdquo;, \u0026ldquo;Stadtmitte\u0026rdquo;, \u0026ldquo;Feuersee\u0026rdquo; or „Schwabstraße\u0026quot; (e.g. Studierendenhotel Stuttgart, Römerhof Vaihingen). From these stations you will need approximately 15-20 minutes to the campus.\nBreakout sessions Detailed schedule for Breakout sessions including room numbers.\nTraining Models using PEtab Fröhlich, Fabian\tPEtab is a standardized file format for specifying parameter estimation problems. The interoperable format is currently supported by 11 different tools, enabling users to benefit from standardized parameter estimation across frameworks based in Python, Julia, R, MATLAB, C++, or GUIs. Although PEtab was initially developed for parameter estimation, recent efforts have extended the format to improve standardization of various adjacent tasks, including: model selection, multi-scale modeling, PKPD and NLME modeling, optimal control, and visualization. In this breakout session, based on audience interests, we will present introductions to PEtab and its extensions, then discuss current efforts to improve PEtab. People unfamiliar with PEtab are welcome to attend, and might first like to check out the docs.\nIntroduction into Nix for scientific software Hauser, Simon\tWorking on software in a team brings all kinds of challenges, especially because everyone has a slightly different development environment. These challenges usually start with onboarding new team members, include complications of moving your local environment to a high performance cluster and end in unreproducible bugs that boil down to \u0026ldquo;\u0026ldquo;works on my machine\u0026rdquo;\u0026rdquo;. Some of these issues can be resolved by providing dependency pinning using poetry or other package managers, but these solutions do not cover the operating system and require additional install documentation that usually contains apt usage. Nix is a general purpose package manager that emerged in the last couple of years that solves these issues, by not just pinning the version of dependencies but also system libraries and tools, like the glibc library, python and also python packages. This session will cover the fundamentals of Nix, including installation, command usage and writing your own custom development environment for a specific software. Participants will learn how to leverage Nix to create reproducible scientific workflows, manage dependencies, and ensure consistent software environments across different systems. Through practical demonstrations and hands-on activities, attendees will gain the skills necessary to integrate Nix into their scientific projects, enhancing both the reliability and portability of their software. Join us to discover how Nix can streamline your scientific software development and deployment processes, fostering greater collaboration and innovation in your research endeavors.\nA COMBINE Standard for Multi-Approach Multi-Scale (MAMS) Modelling Sheriff, Rahuman\tMulti-approach Multi-scale (MAMS) modelling represents a cutting-edge method for modelling and analysis of biological systems, leveraging an integrated suite of diverse modelling frameworks. This multi-approach modelling will encompass a combination of diverse modelling formalisms, such as ordinary differential equations (ODE), partial differential equations (PDE), logical, constraint-based, and agent-based models across multiple scales. These models are intricately tied together to facilitate complex simulations. During the dedicated breakout sessions at Harmony 2021, COMBINE 2021, and HARMONY 2024, we delved into the existing state-of-the-art technologies and standards, including SBML and SED-ML, and their support for multi-approach modelling. These discussions also illuminated the current challenges and gaps within the field. For COMBINE 2024, our objective is to further this conversation by identifying published MAMS models and bringing together the community to enable the creation of novel standards or the enhancement of existing COMBINE standards to support MAMS. This effort aims to foster interoperability and support the rapidly evolving paradigm of MAMS modelling.\nContinuing Work Towards Reproducible Stochastic Biological Simulation Sego, T.J.\tStochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology modeling, stochastic Boolean networks for network modeling, and the Cellular Potts model methodology for multicellular modeling. Proving reproducibility of simulation results is critical to establishing the credibility of a model. To this end, BioModels, the largest repository of curated mathematical models, tests and reports the reproducibility of simulation results for all submitted models when possible. A recent study showed that about 50% of the deterministic ordinary differential equation models on BioModels could not be reproduced when applying criteria for reproducibility to the information provided in their associated publication, reflecting a current crisis of reproducibility. Furthermore, there are no well-accepted metrics or standards for reproducing stochastic simulation results, thus perpetuating the crisis of reproducibility for a broad class of biological models. This breakout session will continue work towards establishing an accepted framework for testing the reproducibility of stochastic simulations in biological modeling. The session will provide a brief overview of recent progress towards defining quantitative measures to determine whether stochastic simulation results can be reproduced, and when results have been reproduced. Attendees will discuss current issues to address towards consensus and broad adoption in relevant modeling communities, as well as future work towards reproducibility of stochastic simulation results using multiscale and complex models.\nSBGN PD: current and future development Rougny Adrien\tVisualization of biological processes plays an essential role in life science research. Over time, diverse forms of diagrammatic representations, akin to circuit diagrams, have evolved without well-defined semantics potentially leading to ambiguous network interpretations and difficult programmatic processing. The Systems Biology Graphical Notation (SBGN) standard aims to reduce ambiguity in the visual representation of biomolecular networks. It provides specific sets of well-defined symbols for various types of biological concepts. SBGN comprises three complementary languages: Process Description (PD), Entity Relationship (ER), and Activity Flow (AF). The XML-based SBGN Markup Language (SBGN-ML) facilitates convenient storage and exchange of SBGN maps. The SBGN languages as well as SBGN-ML are described in detail in specifications (see sbgn.org). This breakout session will focus on the development of SBGN PD. We invite all participants interested in SBGN to join this session, where we will discuss specific issues related to the next version of the PD specification, as well as more open issues related to a future level of SBGN PD.\nCombine spatial multi-cellular modelling with SBML Jörn Starruß\tModularity is key to creating complex multi-cellular models while preserving the accessibility of meaningful submodels. Naturally, composition also encourages reusability and the likes. We want to discuss and establish a common practice how to overlay the spatial dynamics of multi-cellular models with reaction dynamics defined in the SBML standard.\nMost obvious features to be represented separately from the spatial cell dynamics are intra-cellular regulatory systems, inter-cellular communication and spatial reaction-diffusion processes using SBML-spatial. Further issues arise when inter-connecting identical submodels residing in individual cells and the definition of instantaneous assignments upon entity operations (e.g. cell birth \u0026amp; death).\nAs an introductory motivation we will present our latest Morpheus results in embedding spatial reaction-diffusion submodels within moving cells. Using that experience we will sketch a way how to exploit the HMC package to compose SBML models and attach them in a second step to the individual scopes of our spatial model. We hope for a lively discussion on best practice approaches interconnecting spatial multi-cellular modeling and the SBML standard.\nOpenVT\u0026ndash;Developing Framework Description Standards for MultiCellular Agent-Based Virtual Tissue Models Glazier, James\tMany simulation frameworks implement multicellular agent-based models using a variety of methodologies (center model, vertex model, Cellular Potts model, finite-element mechanics,\u0026hellip;.) and support a variety of biological and mathematical processes it can be often confusing and time consuming to for a researcher to know which simulation framework can fulfill their modeling needs. This session will discuss an approach to defining and categorizing simulation framework capabilities. The session will start with an overview of the various methods employed in multicellular simulations, highlighting their unique features and common challenges. It will present our approach to describing framework descriptions in a standardized way followed by discussion on this approach.\nOpenVT\u0026ndash;MultiCellular Agent-Based Virtual Tissue Models: Defining Topics and Priorities Glazier, James\tVirtual Tissues (VT), agent based multicellular modeling has become indispensable in understanding complex biological phenomena, from tissue development to disease progression. But the diversity in simulation methods poses challenges in reproducibility, modularity, reusability, and integration for multiscale models, leading to a fragmented ecosystem and hindering growth. The OpenVT Community is trying to address these challenges by bringing siloed research groups together to improve the sharing of VT knowledge. The OpenVT Community supports the expansion of and broader adoption of multicellular modeling beyond academic research labs into greater industry practice. Development of best practices and better reproducibility will ultimately lead to models that more closely follow FAIR (Findable, Accessible, Interoperable, and Reusable) principles, leading to wider use in therapeutic approaches, toxicology, drug discovery and personalization of testing and treatment. This session aims to discuss current progress undertaken by the OpenVT community towards a shared ecosystem and look to attendees for insight into what they believe will encourage broader adoption of community guidelines.\nOpenVT\u0026ndash;Developing Reference Models for Multicellular Agent-Based Virtual Tissue Models Glazier, James\tAn increasing number of packages implement multicellular agent-based models using a variety of methodologies (center model, vertex model, Cellular Potts model, finite-element mechanics,\u0026hellip;.). In principle a set of underlying biological and physical processes should yield the same result independent of the package in which they are implemented. However, at the moment, comparison between methodologies or even between different packages implementing the same methodology, is quite challenging. As a first step to building a shared understanding of modeling capabilities and to improve rigor and reproducibility, we define a minimal set of standard reference models which should be implemented in each framework to illustrate their capabilities and reveal hidden discrepancies of approach. This session will discuss these efforts and look for feedback from attendees.\n Tutorials Workshop: refineGEMs and SPECIMEN for automated model reconstruction and annotations Döbel, Gwendolyn O.\nMetabolic model reconstruction usually relies on several cumbersome steps. Different tools exist, which are only partially automated and need to be connected manually. Our aim is to simplify and reduce the manual workload. Thus, we developed the toolbox refineGEMs and the workflow collection SPECIMEN. A stable release of refineGEMs was already used in practice. Both tools are currently under active development (enhancement and extension).\nThis workshop aims to give the attendees a brief introduction to automatic metabolic modelling with the tools refineGEMs and SPECIMEN. As part of the workshop, an open discussion will be held about issues arising from automatic energy-generating cycle (EGC) dissolution and gap filling.\nBiological and Biophysics Simulation in Tissue Forge: Introduction and Guided Simulation Building Sego, T.J.\nTissue Forge is open-source simulation software for interactive particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular, using a simple interface. While Tissue Forge is designed to simplify solving problems in complex subcellular, cellular and tissue biophysics, it supports applications ranging from classic molecular dynamics to agent-based multicellular systems with dynamic populations. Tissue Forge users can build and interact with models and simulations in real-time and change simulation details during execution, or execute simulations off-screen and/or remotely in high-performance computing environments. Tissue Forge provides a growing library of built-in model components along with support for user-specified models during the development and application of custom, agent-based models. Tissue Forge includes an extensive Python API for model and simulation specification via Python scripts, an IPython console and a Jupyter Notebook, as well as C and C++ APIs for integrated applications with other software tools. Tissue Forge supports installations on Windows, Linux and MacOS systems and is available for local installation via conda. This tutorial introduces the basic concepts, modeling and simulation features, and some relevant modeling applications of Tissue Forge through guided simulation scripting. Tutorial concepts will introduce basic Tissue Forge modeling concepts and simulation features through the development of interactive simulations in Python. Attendees are encouraged, but not required, to code along as the tutorial interactively develops and tests simulations in multicellular and biophysics modeling applications.\nMorpheus: A user-friendly simulation framework for multi-cellular systems biology Starruß, Jörn and Brusch, Lutz\n\u0026ldquo;Multi-cellular modeling and simulation become increasingly important to study tissue morphogenesis and disease processes. This tutorial introduces Morpheus in an overview presentation with live demos and hands-on exercises runnable in sync on the presenter\u0026rsquo;s and your own laptop. The focus lies on importing SBML models into Morpheus, extending them in space as reaction-diffusion processes and automatically \u0026ldquo;\u0026ldquo;cloning\u0026rdquo;\u0026rdquo; them into many individual cells that can dynamically interact. Also, own modeling ideas can be explored with the help of a tutor. Morpheus offers modeling and simulation of multi-cellular dynamics in a Graphical User Interface (GUI) without the need to program code. It uses the domain-specific language MorpheusML to define and simulate multicellular models in 3D space including the most common cell behaviors and tissue mechanics. Morpheus is open-source software and provides readily installable packages for macOS, Windows, Linux. Please download before the tutorial and have a look around the homepage incl. \u0026gt;90 example models.\n  Talks  Results and Lessons learnt from the community-level project on “Fostering the uptake of RDA indicators in Systems Biomedicine as a measure for model quality and FAIRness within the COMBINE community”  Irina Balaur Biosimulation models incorporating multi-layered information have been developed to explore complex disease mechanisms. While these models have potential for diagnosis and therapy support, their clinical use is limited by unclear specifications on settings and kinetics, hampering reusability and reproducibility. Adhering to the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) can enhance the credibility and reproducibility of these models.\nIn this talk, we will focus on the results and lessons learned from our project on applying RDA indicators for the FAIR evaluation of biosimulation models within the COMBINE community . Funded by the EOSC Future, the project focused on developing community-level guidelines for FAIR model design and a semi-automatic FAIR evaluation tool for COMBINE models. We adapted the RDA FAIR indicators template from the IMI FAIRplus project to cover the specificities of the COMBINE computational simulations. The semi-automatic FAIR assessment tool enables some RDA FAIR indicators to be filled automatically.\nWe will also discuss the major challenges and strategies for achieving a community-accepted set of FAIR indicators specific to COMBINE resources. To address these challenges, we organized workshops and training sessions within the RDA and COMBINE communities, and engaged in transparent communication, online dissemination, and involvement acknowledgment. All components of our work are open, freely accessible, and connected via our project website to major frameworks like Zenodo for dissemination materials and GitHub for code files.\nWe also collaborated with other relevant projects on FAIR data and infrastructure. We will conclude by exemplifying our work on the FAIR assessment of the MINERVA platform, supporting the Disease Maps Project, and the ongoing development of a FAIR-calibration framework for reporting guidelines of AI-related studies in healthcare to enhance reproducibility and open science.\nCompuTiX: A library for agent based modeling (not only) at a tissue-scale  Jiří Pešek and Dirk Drasdo In recent years, many studies have shown that the tissue microarchitecture along with the mechanical environment has a crucial yet poorly understood impact on the biological processes inside living tissues This have a significant impact on progression of any potential disease or treatment. The limitations of in-vivo imaging techniques together with the small scale and isolated nature of many in-vitro experiments, makes these systems a suitable candidate for in-silico approach, where initial in-vitro experiments can be used to formulate and tune the underlying models and in-vivo imaging is then used to generate a patient specific setup. In particular, an agent based models, where the global effect is achieved by interaction between many, relatively simple, entities, are suitable to capture the spatial and behavioral heterogeneity and complexity of living tissues. In this talk we will present a new open-source computational library, CompuTiX, suitable for agent based simulations of tissues, organoids and more. We will split the talk into two parts. In the first part we will briefly introduce basic bio-physical models starting from simple center based models to more complex models like deformable cell model. In the second, more technical, part we will discuss the architecture of the library, design choices, trade-offs and challenges in our goal to provide a versatile and extensible platform for agent based simulations.\n Networks, simple models and model diversity in the description of biological systems Marc-Thorsten Hütt \u0026ldquo;My talk will address three distinct, but interrelated, topics: (1) networks as structural models to interpret high-throughput data; (2) the distinction between mathematical models and their computer implementations; (3) simple models vs. complicated, parameter-rich models.\nSystems biology and systems medicine frequently use network-based strategies for data interpretation and data contextualization. These methods, at times, lack standardization and comparability. Here I briefly discuss, how such methods work, and which implicit hypotheses are associated with them.\nThe formal representation of a mathematical model is often incomplete, compared to the details required for an implementation of the model to run numerical simulations. Implementation differences can in principle lead to drastically different results. For the case of models of excitable dynamics, I illustrate this point, showing that even the simplest models can display such implementation differences.\nLastly, residing on the topic of simple models, I briefly draw the attention to the co-existence of parameter-rich and simple models of biological systems, outlining a few pros and cons and caveats. \u0026quot;\n Energy and Information in Gene Regulation  Heinz Köppl The essence of cellular function is to maintain a non-equilibrium state through an influx of chemical energy. In particular gene regulation involves several active steps that require energy carriers such as ATP. Thermodynamic uncertainty relations tell us that reducing fluctuations in molecular systems comes at the expense of energy consumption which in turn is related to the rate of entropy production. In this talk I will make this notion more concrete for Markov models of chemical reaction networks and in particular for simple models of gene expression. We will also introduce an operational notion of precision for a molecular signal processing systems using information theory. We show how entropy production rates provides bounds on the achievable information throughput for simple gene expression channels. We also discuss how this analysis can help in designing regulatory circuits in synthetic biology that are energy efficient and yet precise.\n Computational design of biological receivers using multi-scale models and data standards  Göksel Misirli Engineering genetic regulatory circuits that sense external molecules and respond is essential for developing diverse biological applications. As the complexity of designs increases, a model-driven design process becomes desirable to explore large design spaces that involve different biological parts and parameters. Moreover, the amount of these molecules reaching a receiver is usually assumed to be constant, and the diffusion dynamics and the interference caused by late-arriving molecules and the cellular dynamics are often not integrated. Additionally, each molecule type may represent a single biological signal and be unsuitable for encoding and decoding multiple data bits. Here, we present the virtual parts repository, a computational framework that provides modular, reusable and composable models. The framework facilitates automating the design of predictable applications via simulations. It builds on the Systems Biology Markup Language to model cellular behaviour and the Synthetic Biology Open Language to capture the details of genetic circuits. We then extend this automation approach to design the end-to-end transmission of signalling molecules from a transmitter to cellular receivers for multi-bit data communications. The resulting framework can be used to understand the cellular response for a sequence of custom data bits, each representing a group of molecules released from a transmitter and diffusing over a molecular channel. The framework validates and verifies various communication parameters and identifies the best communication scenarios. We also present a novel algorithm to minimise signal interference by employing equalisation techniques from communication theory. Our data standards-enabled and multi-scale modelling workflow combines engineering genetic circuits and molecular diffusion dynamics to encode and decode data bits, design efficient cellular signals, minimise noise, and develop biologically plausible applications.\n The past, present and possible futures  Herbert Sauro It has almost been 25 years since Hiroaki Kitano initiated the development of SBML as part of the ERATO project. Together with Bolouri, Doyle, Finney, Hucka, myself and a number of key stakeholders (who continue to meet at COMBINE), we published the first draft and software support libraries for the SBML specification. Around the same time we also saw the publication of the specification for CellML that was a more mathematically oriented proposal. What resulted was most unexpected, the emergence of a new vibrant ecosystem which stimulated further development, created a host of new ancillary standards as well as the indispensable BioModels repository. That ecosystem still exists today. In this talk I will review what I feel remains to be done or is incomplete, what new modeling challenges we face, and describe what the center of model reproducibility in the US is doing in terms of software provision. In particular I will describe a number of new client-based web tools and desktop apps. The client-based tools are unusual in that they can be hosted from any free basic server such as a GitHub, Neocities or Cloudflare page. This makes such apps very low maintenance and tend to persist long after funding stops. Examples from our center include a model annotation (AWE) platform, a simple model checking app (ratesb), a high speed BioModels cache, a reproducibility portal, a model verification service, a new SBML/Antimony web utility, a Biosimulators/Biosimulations repository, a new SBML compliant desktop app, a number of new python packages for network visualization, a new desktop network editor (Alcuin), new extensions to Antimony (See talk by Lucian Smith), a standard protocol for multi-scale modeling (See talk by Eran Agmon), and the first model credibility hackathon held this summer.\n Improving Curation: Biomodels and Annotation  Lucian Smith The BioModels Database has over 1000 curated models from published papers. Curators at the EBI ensure that the model can be used to reproduce at least one figure from the paper, and extensively annotate the model as well. However, until the advent of SED-ML, it was impossible to store what the curator did to reproduce the model in a standard format, and until more widespread use of SED-ML, it was impossible to reliably validate any SED-ML that was produced. The Center for Reproducible Biomedical Modeling has produced new SED-ML interpreters and validators that have bridged this gap, and we have partnered with the EBI to ‘retro-curate’, as far as possible, the curated branch of BioModels, to include validated SED-ML, which we have then tested using the SED-ML interpreters on multiple simulation engines. In addition, we have extended the Antimony modeling language, and present the Antimony Web Editor, with particular features useful for adding curation of species, reactions, and parameters.\n MeDaX – two years towards bioMedical Data eXploration  Judith Wodke Research based on clinical care data is gaining attention across the world. However, the quality of clinical care data is generally not maximised for research purposes. Instead, according to economic principles, medical staff and time costs are commonly minimised, rendering the enrichment with sufficient metadata for easy data reuse at least challenging. In addition, a heterogeneous landscape of laws concerning medical data reuse on national, state, and county levels make (international) interoperability an ambitious aim. The MeDaX project was initiated about two years ago and its underlying idea presented at COMBINE 2022: connect and semantically enrich highly diverse clinical and other biomedical data in knowledge graphs (KG) to design, implement, and use graph technologies for innovative data exploration. The MeDaX-KG prototype has been designed and implemented building on the BioCypher framework to harmonise biomedical knowledge graphs and using synthetic patient data. The proof of concept pipeline consists of i) a FHIR input adapter, including an optimisation module for the generically generated graph structure, ii) a semi-automatic data schema generation based on the BioLink ontology, and iii) the visualisation of the resulting MeDaX-KG using Neo4j. Currently, the pipeline is improved, a user interface is implemented, and the first pilot in a german university clinic’s data integration center is set up while the first stable release is prepared.\n The EnzymeML framework: improving efficiency and quality of biocatalytic science  Jürgen Pleiss Biocatalysis is entering a promising era as a data-driven science. High-throughput experimentation generates a rapidly increasing stream of biocatalytic data, which is the raw material for mechanistic and data-driven modeling to design improved biocatalysts and bioprocesses. However, data management has become a bottleneck to progress in biocatalysis. In order to take full advantage of rapid progress in experimental and computational technologies, biocatalytic data should be findable, accessible, interoperable, and reusable (FAIR). The EnzymeML framework provides reusable and extensible tools and a standardized data exchange format for FAIR and scalable data management in biocatalysis 1. To enable storage, retrieval, and exchange of enzymatic data, the XML–based markup language EnzymeML has been developed 2. An EnzymeML document contains information about reaction conditions and the measured time course of substrate or product concentrations. Kinetic modelling is performed by uploading EnzymeML documents to the modelling platforms COPASI or PySCeS or by using the JAX platform. The rate equation and the estimated kinetic parameters are then added to the EnzymeML document. The EnzymeML document containing the experimental and the modelling results is then uploaded to a Dataverse installation or to the reaction kinetics database SABIO-RK. The workflow of a project is encoded as Jupyter Notebook, which can be re-used, modified, or extended The feasibility and usefulness of the EnzymeML toolbox was demonstrated in six scenarios, where data and metadata of different enzymatic reactions are collected, analysed, and uploaded to public data repositories for future re-use 3. FAIRification of data and software and the digitalization of biocatalysis improve the efficiency of research by automation and guarantee the quality of biocatalytic science by reproducibility4. Most of all, they foster reasoning and creating hypotheses by enabling the reanalysis of previously published data, and thus promote disruptive research and innovation.\n preCICE – A General-Purpose Simulation Coupling Library  Benjamin Ückermann preCICE is an open-source coupling software for partitioned multi-physics and multi-scale simulations including PDE-PDE and PDE-ODE coupling. Thanks to the software\u0026rsquo;s library approach (the simulations call the coupling) and its high-level API, only minimally-invasive changes are required to prepare an existing (legacy) simulation software for coupling. Moreover, ready-to-use adapters for many popular simulation software packages are available, e.g. for OpenFOAM, SU2, CalculiX, FEniCS, and deal.II. For the actual coupling, preCICE offers methods for fixed-point acceleration (quasi-Newton acceleration), fully parallel communication (MPI or TCP/IP), data mapping (radial-basis function interpolation), and time interpolation (waveform relaxation). Today, although being an academic software project at heart, preCICE is used by more than 100 research groups in both academia and industry. In this presentation, I introduce the basic concepts of preCICE and discuss existing and potential applications in biology.\n Reproducible tools for dealing with highly variable data  Nicole Radde In the biomedical context, data is often sparse, and replicates show a high variability. This is because complex procedures, costs, and ethical aspects constrain measurements. Sparsity and high variability pose a challenge for modeling, especially when building models aiming to capture quantitatively dynamic responses. Here, we present two complementary approaches we developed in our group to deal with sparse and variable data. Bayesian Modeling of Time Series Data (BayModTS) uses a Bayesian approach and a simulation model to process sparse and highly variable serial data. BayModTS can be used to quantify uncertainty in the observed process or as a noise filtering approach, as we will demonstrate with selected examples. Second, Eulerian Parameter Inference (EPI) formulates the parameter estimation problem for a simulation model from experimental data as a stochastic inverse problem and infers a parameter distribution that can reproduce the variability of the input data. Both approaches are implemented as documented software packages that use standards such as SBML or PEtab. In my talk, I will briefly explain our methods and discuss the current challenges regarding reproducibility and FAIR principles from a modeler’s perspective.\n  Lightning talks Modeling and simulation using industrial standards Modelica, FMI and web components. - Lightning talk session 2 Tomas Kulhanek We use industrial standard Modelica to express complex models of human physiology [1,2]. Recently we have published enabling technology that allows to export complex models in standard functional mockup interface API (FMI) as a web component to be integrated with other web standards and technologies to create modern web application. Thanks to it the models does not necessarry need to be implemented in Modelica language, but and standard FMI needs to be implemented by other standards to compute model derivatives and do simulation step using a prefered numerical method.\nUtilizing Nix for rapid BayModTS development - Lightning talk session 3 Hauser, Simon BayModTS, a python project for FAIR Bayesian Modelling of Time Series workflows, has a complex setup that requires users of that software to install and compile multiple python packages that have native C dependencies. This is a complex endeavor and currently it is not possible to fully resolve these issues using poetry install. We present a solution that utilizes a general purpose package manager called Nix, that guarantees that a package and all its dependencies can be built reproducibly. This package manager can be used to build all kinds of software packages, including C libraries and python packages, which we need to realize our solution.\nBiological and Biophysics Simulation in Tissue Forge - Lightning talk session 4  Sego, T.J. Tissue Forge is open-source simulation software for interactive particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular, using a simple interface. While Tissue Forge is designed to simplify solving problems in complex subcellular, cellular and tissue biophysics, it supports applications ranging from classic molecular dynamics to agent-based multicellular systems with dynamic populations.\nA COMBINE Standard for Multi-Approach Multi-Scale (MAMS) Modelling - Lightning talk session 1  Sheriff, Rahuman Multi-approach Multi-scale (MAMS) modelling represents a cutting-edge method for modelling and analysis of biological systems, leveraging an integrated suite of diverse modelling frameworks. This multi-approach modelling will encompass a combination of diverse modelling formalisms, such as ordinary differential equations (ODE), partial differential equations (PDE), logical, constraint-based, and agent-based models across multiple scales. These models are intricately tied together to facilitate complex simulations.\nContinuing Work Towards Reproducible Stochastic Biological Simulation - Lightning talk session 3  Sego, T.J. Stochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology modeling, stochastic Boolean networks for network modeling, and the Cellular Potts model methodology for multicellular modeling.\nMorpheus model repository: Experiences with reproducible multi-cellular models - Lightning talk session 1  Brusch, Lutz \u0026ldquo;Collaborative modeling and simulation become increasingly important for studying self-oganization, patterning, morphogenesis and disease processes from the intracellular to the tissue and organ scales. To support collaborations, we have developed the Morpheus model repository. This model repository is an open access and citable platform for publishing, sharing and archiving multi-scale and multi-cellular models that are encoded in the model description language MorpheusML.\nComputational Model Development Using SBML: sbmlutils, sbm4humans, cy3sbml - Lightning talk session 4  König, Matthias \u0026ldquo;The Systems Biology Markup Language (SBML)(doi 10.15252/msb.20199110) is recognized as the standard framework for representing and exchanging complex mathematical models in biological systems research. One of the primary challenges faced by newcomers in computational biology is the encoding and development of ordinary differential equation (ODE) models within the SBML framework. Addressing this hurdle, we introduce two innovative Python tools: sbmlutils, sbml4humans, and the Cytoscape application cy3sbml. These tools collectively streamline the process of SBML model creation, enhancing both the programmatic aspect and the user experience.\nOpenVT\u0026ndash;Developing Framework Description Standards for MultiCellular Agent-Based Virtual Tissue Models - Lightning talk session 3  Glazier, James Many simulation frameworks implement multicellular agent-based models using a variety of methodologies (center model, vertex model, Cellular Potts model, finite-element mechanics,\u0026hellip;.) and support a variety of biological and mathematical processes it can be often confusing and time consuming to for a researcher to know which simulation framework can fulfill their modeling needs. In our breakout session, we will discuss an approach to defining and categorizing simulation framework capabilities. (Zoom link; was iu.zoom.us/meeting/register/tZUlcu6hpjoiG9OLZ1rGcrOfWkf49p4uVtjo)\nOpenVT:MultiCellular Agent-Based Virtual Tissue Models: Defining Topics and Priorities for Working Groups and Virtual Workshops - Lightning talk session 1  Glazier, James \u0026ldquo;Virtual Tissues (VT), agent based multicellular modeling has become indispensable in understanding complex biological phenomena, from tissue development to disease progression. But the diversity in simulation methods poses challenges in reproducibility, modularity, reusability, and integration for multiscale models, leading to a fragmented ecosystem and hindering growth. The OpenVT Community is trying to address these challenges by bringing siloed research groups together to improve the sharing of VT knowledge. (Zoom link; was iu.zoom.us/meeting/register/tZUlcu6hpjoiG9OLZ1rGcrOfWkf49p4uVtjo)\nOpenVT\u0026ndash;Developing Reference Models for Multicellular Agent-Based Virtual Tissue Models - Lightning talk session 4  Glazier, James An increasing number of packages implement multicellular agent-based models using a variety of methodologies (center model, vertex model, Cellular Potts model, finite-element mechanics,\u0026hellip;.). In principle a set of underlying biological and physical processes should yield the same result independent of the package in which they are implemented. However, at the moment, comparison between methodologies or even between different packages implementing the same methodology, is quite challenging. As a first step to building a shared understanding of modeling capabilities and to improve rigor and reproducibility, we define a minimal set of standard reference models which should be implemented in each framework to illustrate their capabilities and reveal hidden discrepancies of approach. (Zoom link; was iu.zoom.us/meeting/register/tZUlcu6hpjoiG9OLZ1rGcrOfWkf49p4uVtjo)\nA functional tissue unit approach to understanding lung function in health and disease - Lightning talk session 2  Li, Ruobing The primary functional tissue unit of the lungs is the acinus. An acinar unit brings together diverse functions, including airflow, blood flow, gas exchange, mechanical deformation and the effect of surfactant on this, and fluid transport from the blood to the lymphatic vessels. Existing models of varying geometric complexity have been developed to simulate lung mechanical behaviours and various fluid transport, currently as separate systems. This study addresses this gap by developing a respiratory FTU that integrates these different models to simulate acinar function and link this to represent whole lung function. Model implemented by CellML, Fortran, and Python. By integrating these individual models, we aim to provide a better understanding of the interactions and dependencies within the lungs, essential for simulating lung function in health and disease.\nUpdates to the Systems Biology Graphical Notation: A Standardized Representation of Biological Maps - Lightning talk session 1  Luna, Augustin Visualization of biological processes plays an essential role in life science research. Over time, diverse forms of diagrammatic representations, akin to circuit diagrams, have evolved without well-defined semantics potentially leading to ambiguous network interpretations and difficult programmatic processing. The Systems Biology Graphical Notation (SBGN) standard aims to reduce ambiguity in the visual representation of biomolecular networks.\nA Standardized Protocol for Integrative, Multiscale Modeling - Lightning talk session 1  Moraru, Ion We are developing a standardized protocol for multi-algorithmic model composition, based on standardized schemas for process interfaces, composition patterns, and orchestration patterns. This will provide the foundation for robust infrastructure for systems biology models. The BioSimulators project aims to establish this protocol, ensuring reproducibility, tool compatibility, and \u0026ldquo;plug-and-play\u0026rdquo; integration of new processes and data.\n  Posters  GEMsembler: a package for comparing and combining ensembles of genome-scale metabolic models to study microbial metabolism Matveishina, Elena  SPECIMEN: Collection of Workflows for Automated and Standardised Reconstruction of Genome-Scale Metabolic Models Brune, Carolin  What is an appropriate standard for modeling microbial communities? Ruth, Beatrice  Shining Light on Single-Cell Dynamics and Heterogeneity: Design and analysis of a hybrid population model for an epigenetic memory system. Klingel, Viviane  TFpredict  Molnár, Dóra Viktória  A Computational Pipeline for Evaluating Agreement Between Large-Scale Models and Diverse Datasets  Huggins, Jonah  CellDesigner5: Biochemical network editor for large-scale modeling. Araki, Taichi  Integrate modelling standards with Energy-based System Analysis Ai, Weiwei  MomaPy: a Python library to work with molecular maps programmatically Rougny, Adrien  The preCICE v3 coupling library and the emerging preCICE ecosystem Chourdakis, Gerasimos  ModelPolisher: Enhancing the Quality and Completeness of Genome-Scale Metabolic Models (GEMs) Eltzner, Dario  Partitioned simulations using the neuromuscular simulation framework OpenDiHu  Homs-Pons, Carme\n SBSCL: A Library of Efficient Java Solvers and Numerical Methods to Analyze Computational Models in Systems Biology  Neumann, Arthur  BayModTS: A Bayesian workflow to process variable and sparse time series data.  Höpfl, Sebastian  Standard compliant data and model management for systems medicine projects  Olga Krebs  The role of standards in defining an ecosystem for Virtual Human Twins (VHTs)  Mayer, Gerhard  Recommendations and requirements for implementing computational models in clinical integrated decision support systems  Golebiewski, Martin  ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"60c62038cfa1637e886f952e901aefdc","permalink":"/author/combine-2024/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2024/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2024 will be a workshop-style event hosted at the University of Stuttgart in Stuttgart, Germany with support of the German Research Foundation (DFG) through the International scientific events program, the Stuttgart Center for Simulation Science (SimTech) and the Stuttgart Research Center Systems Biology (SRCSB).","tags":null,"title":"COMBINE 2024","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2025 was a workshop-style event hosted at the University of Wisconsin-Madison, USA.\nLocal organizers are Elebeoba E. May and colleagues.\nWorkshop Location COMBINE 2025 took place on the campus of the University of Wisconsin-Madison in the Pyle Center (702 Langdon St., Madison, WI), within walking distance of hotels, downtown Madison, the state capitol, and Lake Mendota. In addition to great talks, breakouts and meetings, there will be much to enjoy in Madison: food (known for the cheese and beer), football, lakes, great bike trails, museums, and one of the largest outdoor farmers markets in the USA. Many restaurants are within walking distance of campus and venue. Schedule: COMBINE 2025 Workshop Agenda (Final)   COMBINE 2025 Participants  Participants that have registered on Eventbrite and provided consent on Google registration form.  Invited Keynotes and Plenary Speakers  Belinda Akpa, \u0026nbsp;\tUniversity of Tennessee-Knoxville, USA Sasitharan Balasubramaniam, \u0026nbsp; University of Nebraska-Lincoln, USA William Bentley, \u0026nbsp; University of Maryland-College Park, USA Gheorghe Craciun, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Adriana Dawes, \u0026nbsp;\tThe Ohio State University, USA Bernard de Bono, \u0026nbsp; Indiana University, USA \u0026 University of Auckland, New Zealand John Denu, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Anthony Gitter, \u0026nbsp;\tMorgridge Institute \u0026 University of Wisconsin-Madison, USA Jo Handelsman, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Herbert Levine, \u0026nbsp; Northeastern University, USA Erica Majumder, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Megan Mcclean, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Ion Moraru, \u0026nbsp;\tUConn Health, USA Chris Myers, \u0026nbsp;\tUniversity of Colorado-Boulder, USA David Nickerson, \u0026nbsp; Auckland Bioengineering Institute, University of Auckland, New Zealand Brian Pfleger, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA Sushmita Roy, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA James Sluka, \u0026nbsp; Indiana University - Bloomington, USA Lucian Smith, \u0026nbsp; University of Washington, USA John Yin, \u0026nbsp;\tUniversity of Wisconsin-Madison, USA  Arrival and Transportation There are several airports near Madison, Wisconsin and the University of Wisconsin-Madison, the location of the workshop.\n Dane County Regional Airport (MSN): 6 miles from downtown, nonstop flights to major hubs. General Mitchell International (MKE): 80 miles east, more flight options. Chicago O\u0026rsquo;Hare International (ORD): 130 miles southeast, ideal for international travel Chicago Midway International (MDW): 140 miles southeast, budget-friendly with Southwest  Ground Transportation  Direct flights to MSN are available from major US cities (Chicago, Washington, DC). If flying into MSN you can use ride share or taxi to get to the university. If flying into airports close to Madison, WI (e.g., MKE and ORD) there are reasonably priced regional buses with stops on UW-Madison's campus. Regional busses Accommodations and Conference Hotels  There are two conference hotels for COMBINE 2025, UW-Madison's Union South Hotel and the DoubleTree Hotel. A block of rooms have been held and are available for workshop participants to book stays from October 19th-24th at a nightly rate of $186 USD (exclusive of taxes and any applicable fees). Reservations must be made by September 28, 2025.  DoubleTree Hotel Downtown Madison COMBINE 2025 - DoubleTree is 0.4 miles from the Pyle Center with complimentary downtown and airport shuttle service. Union South Hotel COMBINE 2025  - Union South is 0.8 miles from the Pyle Center with complimentary parking.   Anti-Harassment Policies  The COMBINE community is dedicated to providing a harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of participants in our meetings, email list, and other communication mechanisms in any form. Sexual language and imagery is not appropriate for any of these venues, including talks, workshops, parties, email lists, Twitter and other online media. Participants in our meetings and discussions violating these rules may be sanctioned or expelled from our mailing lists and our meetings without a refund at the discretion of the COMBINE coordinators. This policy is linked on the COMBINE website.  Child Care Availabilty \u0026 Local Resources  COMBINE 2025 does not provide child care, however local resources for short-term child care may be available through Care.com or similar services. Additional information/resources will be shared as available. Support ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"10e4d54cabb9c0c2b0c276b0577c815a","permalink":"/author/combine-2025/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2025/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology and related fields. COMBINE 2025 was a workshop-style event hosted at the University of Wisconsin-Madison, USA.","tags":null,"title":"COMBINE 2025","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. COMBINE 2026 will be a workshop-style event hosted at Keele University, UK.\nLocal organisers are Goksel Misirli, Metehan Unal, and Roberto Galizi.\nConfirmed Invited Speakers  Geoff Baldwin, Centre for Engineering Biology, Imperial College, UK Rahuman Sheriff, European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), UK Gary Mirams, Centre for Mathematical Medicine \u0026amp; Biology, University of Nottingham, UK  Workshop Location COMBINE 2026 will take place at Keele University in Newcastle under Lyme, Staffordshire, ST5 5NS, United Kingdom. The conference will be held at the Smart Innovation Hub (also known as Innovation Centre 6).  The Think Lab (LG0.31) will be used as the main room on the lower ground floor. Please see the floor plan. A lift is available from the upper ground floor. The lower ground floor also has direct access from outside. Please contact us should you require assistance prior to your arrival. In addition to the main room, three breakout rooms will be available after 12:00. All of the rooms are located on the lower ground floor.  Open Innovation - LG.035 (up to 34 people) Executive Boardroom - LG.035 (up to 20 people) Boardroom - LG.036 (up to 14 people)  Schedule The schedule will be available here. Posters The posters will be displayed on Monday, 7 Sep. A0 poster boards will be available in the Atrium. Please make sure to submit your poster abstracts. COMBINE Dinner The registration also includes a three course banquet dinner, which will be on Monday at 19:00 and held in Salvin Room at Keele Hall (number 15 on the Keele campus map on page 3). Please advise the organisers if you have any allergies, intolerances or special dietary requirements, using the registration form. Arrival and Transportation Please see the Delegate Information Sheet on page 2  for travelling to Keele. You will find information about the nearby airports, and getting to Keele by rail or car. Additional information can be found at: https://keele-conference.com/delegates-visitors-how-to-get-to-keele/  The venue, Smart Innovation Hub, is marked as number 51 (close to the main university entrance) on the Keele campus map on page 3. The postcode for the building is ST5 5NS.  Parking For those who plan to arrive by car, please see the car parking section on page 1. You must register your car prior to arrival at Keele. We will share a link for you to register your details closer to the event. If you have any questions, please contact the organisers. Once registered, car parking is available in Plot 7 , also known as A3 (see page 3 on the Delegate Information Sheet). Accommodation Some accommodation options are listed below. There are several other options available in Newcastle-under-Lyme and Stoke-on-Trent. Some of the nearby hotels:  Courtyard by Marriott Keele Staffordshire: The hotel is on campus and just opposite the venue. 95.00 GBP per night if you book using this link. This rate is valid for reservations between 6 and 10 September 2026. Number 45 (close to the main university entrance) on the Keele campus map on page 3. Holiday Inn - Newcastle under Lyme Travelodge - Newcastle under Lyme There are also other options, such as Premier Inn and Hilton.  Meals The registration includes a two-course buffet lunch, which will be in the Atrium on the lower ground floor. Please advise the organisers if you have any allergies, intolerances, or special dietary requirements using the registration form. Tea and coffee will also be provided during the breaks. There is also a small cafe on the lower ground floor, which offers a selection of teas, coffees, breakfast, lunch, snacks, and sweet treats. For more options, please see below:\nhttps://www.keele.ac.uk/study/student-life/campuscommunity/food-and-drink/restaurantsbarsandcafes/\nhttps://www.keele.ac.uk/study/student-life/campuscommunity/food-and-drink/shopsandvending/\nPower outlet G-type plugs are used in the UK.\nVisa Please check here if you require a visa. If you need a letter to support your application, please contact the organisers. Additionally, if you need confirmation that a talk, poster, or breakout session will be accepted before the confirmation deadline, please contact the organisers. Support We gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BB/Z517367/1), the School of Computer Science and Mathematics at Keele University, and the EU H2020 grant MSCA-RISE-2020-101008140-EffectFact. ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"5364afaccbca8136e3dad0da74983f50","permalink":"/author/combine-2026/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2026/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. COMBINE 2026 will be a workshop-style event hosted at Keele University, UK.","tags":null,"title":"COMBINE 2026","type":"authors"},{"authors":["COMBINE Archive"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"b4d65c2efbe10aba386d09da18bd8730","permalink":"/author/combine-archive/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-archive/","section":"authors","summary":"","tags":null,"title":"COMBINE Archive","type":"authors"},{"authors":["COMBINE Archive Metadata"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"fd853f007c36193512d459ad3117192a","permalink":"/author/combine-archive-metadata/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-archive-metadata/","section":"authors","summary":"","tags":null,"title":"COMBINE Archive Metadata","type":"authors"},{"authors":["David Nickerson"],"categories":null,"content":"I am an associate professor at the Auckland Bioengineering Institute at the University of Auckland, New Zealand. I am an investigator at the Center for Reproducible Biomedical Modeling and involved in many computational modelling projects spanning the cellular, tissue, and whole organ spatial scales. I am actively involved in the development and application of the CellML and SED-ML standards and related software tools. I am also involved in the Physiome Model Repository. I am also the current editor-in-chief at the journal Physiome.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bbaa372fff608476aabc7aacb291845d","permalink":"/author/david-nickerson/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/david-nickerson/","section":"authors","summary":"I am an associate professor at the Auckland Bioengineering Institute at the University of Auckland, New Zealand. I am an investigator at the Center for Reproducible Biomedical Modeling and involved in many computational modelling projects spanning the cellular, tissue, and whole organ spatial scales.","tags":null,"title":"David Nickerson","type":"authors"},{"authors":["Elebeoba May"],"categories":null,"content":"Elebeoba May (Ph.D in Computer Engineering) is an Associate Professor in the Department of Medical Microbiology \u0026amp; Immunology and the Wisconsin Institute for Discovery, and an investigator at the Center for Reproducible Biomedical Modeling and the Center for Theoretical Biological Physics. Her group develops integrated experimental and computational multi-scale, predictive models of biological systems to study infection, microbial stress response, and multicellular communities. Her lab is involved in the development of tools to translate non-SBML metabolic models to SBML for reproducibile modeling.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"8c63db54663bd5c3444876e8b3c0f167","permalink":"/author/elebeoba-may/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/elebeoba-may/","section":"authors","summary":"Elebeoba May (Ph.D in Computer Engineering) is an Associate Professor in the Department of Medical Microbiology \u0026amp; Immunology and the Wisconsin Institute for Discovery, and an investigator at the Center for Reproducible Biomedical Modeling and the Center for Theoretical Biological Physics.","tags":null,"title":"Elebeoba May","type":"authors"},{"authors":["FAIRsharing"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"4a986a6ca3e47b11c2e732dabbf34d0e","permalink":"/author/fairsharing.org/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/fairsharing.org/","section":"authors","summary":"","tags":null,"title":"FAIRsharing.org","type":"authors"},{"authors":["Falk Schreiber"],"categories":null,"content":"Falk Schreiber (Ph.D in Computer Science) is Professor of Practical Computer Science and Computational Life Sciences in the Department of Computer and Information Science at the University of Konstanz, Germany. His interests include computational systems biology, modeling of metabolic systems, analysis and visualisation of biological networks, and immersive analytics in the life sciences. His group is developing various software tools including Vanted and SBGN-ED, as well as databases including MetaCrop. He is also involved in the development of SBGN.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"39ca7387d0268e36a8296dc995daff29","permalink":"/author/falk-schreiber/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/falk-schreiber/","section":"authors","summary":"Falk Schreiber (Ph.D in Computer Science) is Professor of Practical Computer Science and Computational Life Sciences in the Department of Computer and Information Science at the University of Konstanz, Germany. His interests include computational systems biology, modeling of metabolic systems, analysis and visualisation of biological networks, and immersive analytics in the life sciences.","tags":null,"title":"Falk Schreiber","type":"authors"},{"authors":["FROG"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"38a075e2c9834357bca5a24f89ba5b97","permalink":"/author/frog/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/frog/","section":"authors","summary":"","tags":null,"title":"FROG","type":"authors"},{"authors":["FSKX"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"0467e398331f6c528139041c26bf1a39","permalink":"/author/fskx/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/fskx/","section":"authors","summary":"","tags":null,"title":"FSKX","type":"authors"},{"authors":["Gary Bader"],"categories":null,"content":"Gary D. Bader (Ph.D. Biochemistry) works on biological network analysis and pathway information resources as an Associate Professor at The Donnelly Centre at the University of Toronto. He has been involved in leading development of protein interaction and pathway databases and standards, including the BioPAX biological pathways exchange language.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bdf8e545f68d63626768cf9c89631951","permalink":"/author/gary-bader/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/gary-bader/","section":"authors","summary":"Gary D. Bader (Ph.D. Biochemistry) works on biological network analysis and pathway information resources as an Associate Professor at The Donnelly Centre at the University of Toronto. He has been involved in leading development of protein interaction and pathway databases and standards, including the BioPAX biological pathways exchange language.","tags":null,"title":"Gary Bader","type":"authors"},{"authors":["Goksel Misirli"],"categories":null,"content":"Goksel Misirli is a senior lecturer at the School of Computer Science and Mathematics, Keele University, where he co-leads the Biological Systems research group at Keele. His research involves model-driven design of genetic circuits, biological data integration and visualisation, and the development of ontologies. He has been actively involved in the development of the SBOL data model and the SBOL Visual standards. He is also interested in developing computational modelling and annotation strategies using data standards such as SBML.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bdeaf1666fc452d37069f2781385a450","permalink":"/author/goksel-misirli/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/goksel-misirli/","section":"authors","summary":"Goksel Misirli is a senior lecturer at the School of Computer Science and Mathematics, Keele University, where he co-leads the Biological Systems research group at Keele. His research involves model-driven design of genetic circuits, biological data integration and visualisation, and the development of ontologies.","tags":null,"title":"Goksel Misirli","type":"authors"},{"authors":null,"categories":null,"content":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2021 will be an online only meeting similar to COMBINE 2020. Most of the day will be scheduled by the communities as breakouts. In addition, we will have some time each day for community discussion and wrap-ups of breakouts and advertisements for following breakouts.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"d443a710e8af20efbdeaa0a2b989cc13","permalink":"/author/harmony-2021/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2021/","section":"authors","summary":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2021","type":"authors"},{"authors":null,"categories":null,"content":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2022 is going to be organized as a hybrid event with in-person and online participants. In particular:\n April 26 : Online lightning talks (EST afternoon) April 27-29 : in-person breakouts with online participants (8am to 5pm EST) April 30 : online breakouts (8am to 5pm EST)  This event is co-located with 2022 Synthetic Biology: Engineering, Evolution \u0026amp; Design (SEED). Most of the day will be scheduled by the communities as breakouts. In addition, we will have some time each day for community discussion and wrap-ups of breakouts and advertisements for following breakouts.\nPlease see this Google Calendar for the live HARMONY 2022 Schedule. This calendar is only accessible to registered attendees. If you have difficulties accessing the calendar please contact the organisers.\nWorkshop Location Details The site is the Institute for Bioscience and Biotechnology Research (https://www.ibbr.umd.edu). The address is 9600 Gudelsky Drive, Rockville, Maryland 20850 (https://www.ibbr.umd.edu/about)\nAttendees should park in the garage at 9621 Gudelsky Drive, Rockville, Maryland 20850. NIST will validate parking, so attendees don’t have to pay the $15/day fee. Please enter through the double doors located to the right of the flag poles in front of the circular drive.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"544a05fdcbc1b8e31ede68ae5f39c3d0","permalink":"/author/harmony-2022/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2022/","section":"authors","summary":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2022","type":"authors"},{"authors":null,"categories":null,"content":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2023 was hosted by Herbert Sauro and the Center for Reproducible Biomedical Modeling at the University of Washington, Seattle, WA. It was organized primarily as an in-person meeting, with individual breakout sessions responsible for enabling remote participation as needed.\nMost of each day was scheduled by the communities as breakouts. In addition, we had some time each day for community discussion and wrap-ups of breakouts and advertisements for following breakouts.\n Schedule  Here\u0026rsquo;s the full (editable) schedule. Note that many events are scheduled somewhat spontaneously at these events; keep an eye out here or on the COMBINE discord for last-minute changes and additions.\nWorkshop Location Details HARMONY 2023 takes place at the University of Washington (UW, and commonly called \u0026ldquo;U-Dub\u0026rdquo;) in Seattle, Washington. HARMONY 2023 will take place in the William H. Foege Bioengineering building, at 3720 15th Ave NE, Seattle, WA 98195. The building is locked during the day, but will be open the half-hour before the meeting begins. If you arrive later than that, call the department reception at 206-685-2000, or email any of the organizers, or ping us on the COMBINE slack channel.\nThe doors will be locked, so please knock (there\u0026rsquo;s lots of glass), call the Department front desk at (206) 685-2000 or email lpsmith@uw or bioeasst@uw.edu or ping us on the COMBINE Slack!\nArrival and Transportation From the Seatac Airport, take the Link Light Rail north from the airport, and exit at the University of Washington station (NOT Univeristy Street Station; that\u0026rsquo;s a downtown stop). It\u0026rsquo;s a relatively short walk from there to the Bioengineering building. The nearest hotel is slightly further; a little over one mile, so you might want to bus/taxi depending on how much luggage you have. If you get an ORCA card, you can use that on any of the buses or other light rail trips you might take during your stay. There\u0026rsquo;s also a \u0026lsquo;Transit GO Ticket\u0026rsquo; app you should be able to use from your phone (untested by me, but it seems reasonable?).\nHotels The closest hotel to the Bioengineering department is the Univeristy Inn at 4140 Roosevelt Way NE, Seattle, WA 98105; it\u0026rsquo;s about a half mile walk between there and the venue. About a block further (and inexplicably slightly more expensive) is the Watertown Hotel, at 4242 Roosevelt Way NE, Seattle, WA 98105. Any hotel anywhere along the Link Light Rail line will be easy to get to/from as well, as the Univeristy of Washington station is just a half mile away from the venue.\n Attendees  The following is the list of known attendees as of 24/04/2023 23:58:54 UTC (72 total registered, 63 listed below)\n   Name Affiliation Attendance     Eran Agmon UConn Health In person  Multicellular modeling, SBML, SED-ML BioSimulators: https://biosimulators.org, Vivarium: https://vivarium-collective.github.io   Azka Ahmed UW Madison Remotely (virtually)  BioPAX, CellML, COMBINE Archive, Multicellular modeling   Daniel Ajuzie Wisconsin Institute for Discovery Remotely (virtually)  BioPAX, CellML, COMBINE Archive, Multicellular modeling, SBML, SED-ML Our lab develops models at multiple scales ranging from gene network, metabolic network, signal transduction to multicellular models. We model individual cells (bacteria and mammalian) and interactions between cells (microbial and host-microbe).   Steve Andrews UW In person  Spatial modeling, including particularly with the Smoldyn package.   Mihail Anton NBIS, SciLifeLab, Chalmers University of Technology Remotely (virtually)  COMBINE Archive, OMEX Metadata, SBGN, SBML standard-GEM   Bryan Bartley Raytheon BBN In person  SBOL and SBOL Visual   Jacob Beal Raytheon BBN In person  SBOL and SBOL Visual   Frank Bergmann Heidelberg University In person  COMBINE Archive, SBGN, SBML, SED-ML COPASI (copasi.org), basico (basico.rtfd.io), libsbml, libsedml, libcombine   Lutz Brusch Technische Universität Dresden, Germany Remotely (virtually)  Multicellular modeling, SBML COMBINE Archive and OMEX, PEtab, MorpheusML, SBML-Spatial, FAIRSPACE, https://multicellml.org/wiki/doku.php?id=start   Lukas Buecherl University of Colorado Boulder In person  COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML Genetic Design Automation   Kevin Chen University of Washington In person  BioPAX, CellML, COMBINE Archive, NeuroML, OMEX Metadata, SBML, SED-ML   Rafael Costa FCT-NOVA, NOVA School of Science and Technology Remotely (virtually)  COMBINE Archive, SBML   Alan Garny University of Auckland In person  CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SED-ML libOpenCOR and OpenCOR   Tom Gebhardt University of Greifswald Remotely (virtually)  CellML, COMBINE Archive, SBGN, SBML   John Gennari U of Washington In person  BioPAX, CellML, OMEX Metadata, SBML, SBOL and SBOL Visual, SED-ML   James Glazier Indiana University Remotely (virtually)  COMBINE Archive, Multicellular modeling, SBML Replication and annotation of multicellular models   Issa Gnasse Pasteur Institute of Dakar In person  Multicellular modeling, OMEX Metadata Application of Machine learning to find early biomarker in cervical cancer.   Misirli Goksel Keele University Remotely (virtually)  COMBINE Archive, OMEX Metadata, SBML, SBOL and SBOL Visual   Jenn Hadlock Insitute for Systems Biology Remotely (virtually)  BioPAX, OMEX Metadata, SBML NCATS Biomedical Translator   Joseph Hellerstein eScience Institute, University of Washington In person  COMBINE Archive, SBML VSCode-Antimony smart editor, AMAS (Automated Model Annotation System)   Ron Henkel Medical Informatics Laboratory, Institute for Community Medicine, University Medicine Greifswald In person  CellML, COMBINE Archive, SBGN, SBML FAIR   Adel Heydarabadipour University of Washington In person  Multicellular modeling, SBGN, SBML, SBOL and SBOL Visual   Yan-kay Ho University of Cambridge Remotely (virtually)  SBML, SBOL and SBOL Visual https://openbioeconomy.org/research_categories/toolkits/ https://github.com/openplant/openplant_automation_protocols   Diego Jahn Center for Information Services and High Performance Computing (ZIH), TU Dresden, Germany Remotely (virtually)  Multicellular modeling, MultiCellML, MorpheusML Morpheus (https://morpheus.gitlab.io/), MorpheusML Model Repository (https://morpheus.gitlab.io/model/)   Bart Jardine University of Washington In person  COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML Chemical network modeling software and support for SBML   Paul jonas Jost University of Bonn Remotely (virtually)  COMBINE Archive, SBGN, SBML pyPESTO, petab   Jonathan Karr Formic Labs Remotely (virtually)  COMBINE Archive, OMEX Metadata, SBML, SED-ML BioSimulators, BioSimulations   Sarah Keating UCL Remotely (virtually)  SBML   Carlos Lopez Altos Laboratories Remotely (virtually)  Multicellular modeling, SBML, models as computer programs PySB, PyDREAM, PyViPR, all things multiscale modeling   Augustin Luna Harvard Medical School Remotely (virtually)  BioPAX, OMEX Metadata, SBGN, SBOL and SBOL Visual Pathway Commons (pathwaycommons.org); SBGN (sbgn.org); libsbgn (github.com/sbgn/libsbgn); stonpy (github.com/adrienrougny/stonpy)   Karin Lundengård Auckland Bioengineering Institute Remotely (virtually)    Harvey Mannering UCL In person  NeuroML, SBML, SED-ML Tools and standards for single-cell modeling in neuroscience. Currently involved in the ongoing development of libSBML   Elebeoba May University of Wisconsin-Madison Remotely (virtually)  BioPAX, CellML, COMBINE Archive, Multicellular modeling, SBML, SED-ML My lab develops models at multiple scales ranging from gene network, metabolic network, signal transduction to multicellular models. We model individual cells (bacteria and mammalian) and interactions between cells (microbial and host-microbe).   Gerhard Mayer HITS gGmbH Remotely (virtually)  BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, identifiers.org EDITH (European Virtual Human Twin project)   Pedro Mendes UConn Health Remotely (virtually)  OMEX Metadata, SBML, SED-ML COPASI   Blinov Michael UConn Health Remotely (virtually)  BioPAX, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML VCell, BioNetGen, SBML   Tom Mitchell Raytheon BBN Technologies Remotely (virtually)  SBOL and SBOL Visual pySBOL3, SBOL-utilities   Ion Moraru UConn Health In person  COMBINE Archive, Multicellular modeling, SBML, SED-ML http://vcell.org/, http://biosimulations.org/   Sébastien Moretti SIB Swiss Institute of Bioinformatics Remotely (virtually)  SBML https://www.metanetx.org/   Robert Mueller TU Dresden Remotely (virtually)  Multicellular modeling, Morpheus   Chris Myers University of Colorado Boulder In person  COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML SynBioHub, SynBioSuite, iBioSim   David Nickerson Auckland Bioengineering Institute, University of Auckland In person  CellML, COMBINE Archive, OMEX Metadata, SED-ML Physiome Model Repository; Center for Reproducible Biomedical Modeling; Physiome journal   Alexander Patrie Uconn Health Remotely (virtually)  COMBINE Archive, OMEX Metadata, SBML, SED-ML Biosimulators: https://www.biosimulators.org   Tim Rudge newcastle university Remotely (virtually)  Multicellular modeling, SBML, SBOL and SBOL Visual, SED-ML Flapjack, LOICA   Sai Samineni University of Colorado Boulder Remotely (virtually)  SBOL and SBOL Visual, LabOp LabOp, Army Data Standards   Jim Schaff UConn Health Remotely (virtually)  COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML SBML Spatial   T.j. Sego University of Florida In person  CellML, COMBINE Archive, Multicellular modeling, SBGN, SBML, SED-ML CompuCell3D, Tellurium, Tissue Forge   Bilal Shaikh DeepOrigin Remotely (virtually)  CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML Biosimulations   Rahuman Sheriff EMBL-EBI Remotely (virtually)  CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, FROG SBML, BioModels, FROG, FAIRSPACE   Woosub Shin University of Auckland Remotely (virtually)  COMBINE Archive, OMEX Metadata, SBML   Lucian Smith University of Washington In person  CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML Antimony, Tellurium   Hugh Sorby Auckland Bioengineering Institute In person  CellML, COMBINE Archive, SED-ML   Ryan Spangler Altos Labs In person  Multicellular modeling Vivarium   Jörn Starruß Technische Universität Dresden Remotely (virtually)  COMBINE Archive, Multicellular modeling, SBML, SED-ML   Nguyen Tung EMBL-EBI Remotely (virtually)  BioPAX, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML BioModels, COMBINE Archive 2.0   Lorenzo Veschini King\u0026rsquo;s Collge London Remotely (virtually)  Multicellular modeling, OMEX Metadata, SBML   Gonzalo andrés Vidal peña Newcastle University Remotely (virtually)  SBOL and SBOL Visual https://github.com/RudgeLab/PUDU https://github.com/RudgeLab/LOICA   Carolus Vitalis University of Colorado Boulder Remotely (virtually)  SBOL and SBOL Visual   Khoi Vo University of California, Riverside In person  BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML Multiscale modeling of blood clot   Daniel Weindl Helmholtz Munich Remotely (virtually)  SBML, SED-ML, PEtab https://github.com/AMICI-dev/AMICI/ https://github.com/ICB-DCM/pyPESTO/ https://petab.readthedocs.io/en/latest/   Felipe Xavier buson Cambridge University Remotely (virtually)  SBOL and SBOL Visual   Guillermo Yanez feliu Newcastle University Remotely (virtually)  Multicellular modeling, Flapjack Multicellular pattern formation, computational synthetic biology, microscopy, microfluidics and image analysis.   Fengkai Zhang NIAID/NIH In person  COMBINE Archive, Multicellular modeling, SBGN, SBML, SED-ML Simmune    ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"48b3e7adb0c1df2221e23cfb5c1e9a94","permalink":"/author/harmony-2023/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2023/","section":"authors","summary":"The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2023","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2024 will be held at University College London\nLocal organizers are Sarah Keating (s.keating@ucl.ac.uk) and Padraig Gleeson, (p.gleeson@ucl.ac.uk).\nStudents may apply for a travel support from NSF!!! Link is on the LEFT! -- Workshop Location HARMONY 2024 will be held at Centre For Medical Image Computing, University College London, 90 High Holborn, London, WC1V 6LJ.\nOn entering the building turn left to find the reception desk which is hidden away in the left hand corner. The receptionist will let you through to the lifts to the first floor, where somebody will be waiting to let you in.\nYou should have received an invitation to the meeting mailing list harmony_2024 @ googlegroups.com which will be used for communications.\nSchedule The schedule is available below. People who have attended HARMONY in the past will know that this is inclined to change as participants make their own arrangements for conversations/discussions. A link to the editable version will be sent to the mailing list.\nSchedule \nAbstract book \nBreak out booklet\nMore on ARC Tech Socials\nArrival and Transportation London is served by six international airports and twelve major stations including St. Pancras International, which is the Eurostar hub, with multiple direct connections to Europe.\nTravel within London can be done by Tube, Bicycle, Bus, Taxi and more. More information can be found here.\nAccommodations and meals Tea and coffee will be freely available throughout the meeting. In view of the number of people using the building, it may be advisable to bring your own mug!\nA sandwich lunch will also be provided - please make sure you give us the correct information as to which days you will be in attendance when you fill in the registration form.\nVisa Given that the UK is no longer part of the EU, visa requirements may have changed for you. Please check here. If you need a letter to support your application, please contact one of the organizers.\nAdditionally, if you need confirmation that a talk/poster/breakout session will be accepted before the confirmation deadline, please get in contact.\nPower outlet G-type plugs are used in the UK.\nSupport This meeting has been generously supported by the Kavli Foundation.\n Attendees - in person    Name Organization Interests     Alex Fedorec UCL COMBINE Archive, Multicellular modeling, SBML, SBOL and SBOL Visual, SED-ML   Ankur Sinha UCL CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBML, SED-ML, Open Source Brain: https://opensourcebrain.org   Augustin Luna National Library of Medicine BioPAX, SBGN, SBML, sbgn.org; pathwaycommons.org   Carolus Vitalis University of Colorado Boulder SBOL and SBOL Visual   Casey Chen UCL Multicellular modeling, SBML, SBOL and SBOL Visual   Chris Barnes UCL Multicellular modeling, SBML, SBOL and SBOL Visual   Chris Myers CU Boulder COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML, iBioSim, SynBioHub, SBOLCanvas   Dilan Pathirana University of Bonn CellML, SBML, SED-ML, PE-TAB, PEtab extensions (timecourses, model selection, NLME)   Eleonora Bernasconi University of Herfordshire, Hatfield, Hertfordshire, AL10 9AB, UK NeuroML, I am a PhD student working on a large scale, biologically realistic model of the cerebellar cortex.   Fabian Fröhlich The Francis Crick Institute BioPAX, SBML, PE-TAB   Felipe Xavier Buson Universit of Cambridge SBOL and SBOL Visual   Fengkai Zhang NIH COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, Simmune. SBML-Multi and rule-based model   Frank Bergmann BioQUANT, Heidelberg University, INF 267 COMBINE Archive, SBML, SED-ML, PE-TAB, FROG, COPASI - modeling, simulation and analysis environment for biochemical networks, https://copasi.org. basico - a convenient python interface to COPASI, https://basico.rtfd.io/   Georgie Sorensen University of Bristol SBOL and SBOL Visual   Goksel Misirli Keele University, School of Computer Science and Mathematics Multicellular modeling, OMEX Metadata, SBML, SBOL and SBOL Visual, SBOL3 Java Library   Gonzalo Vidal University of Colorado Boulder, Boulder, Colorado, US SBML, SBOL and SBOL Visual, https://gonza10v.github.io/   Hugh Sorby Auckland Bioengineering Institute CellML, SED-ML   Ion Moraru UConn Health, Farmington, CT, USA COMBINE Archive, NeuroML, OMEX Metadata, SBML, SED-ML, BioSimulations, VCell   Jörn Starruß Technische Universität Dresden CellML, Multicellular modeling, SBML, SED-ML, PE-TAB, MorpheusML, Morpheus,   Jona Leka UCL NeuroML   Kathleen Zhang UCL BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, PE-TAB, FROG   Louie Destouches UCL Multicellular modeling, SBML, SBOL and SBOL Visual   Lucian Smith University of Washington, Seattle, WA COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML, FROG, Tellurium, Roadrunner, and Antimony (https://tellurium.readthedocs.io/)   Lukas Buecherl University of Colorado Boulder COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML   Manuel Lera Ramirez UCL SBOL and SBOL Visual, https://genestorian.org/   Maren Philipps University of Bonn; LIMES Institute COMBINE Archive, Multicellular modeling, SBML, PE-TAB, PEtab, pyPESTO   Michael Blinov Center for Cell Analysis and Modeling, UConn Health, Farmington, CT, USA BioPAX, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, http://vcell.org; http://MolClustPy.github.io; http://www.ModelBricks.org/   Natasa Miskov-Zivanov University of Pittsburgh BioPAX, COMBINE Archive, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, BioRECIPE (melody-biorecipe.readthedocs.io); ACCORDION (melody-accordion.readthedocs.io); CLARINET (melody-clarinet.readthedocs.io)   Padraig Gleeson UCL, London CellML, Multicellular modeling, NeuroML, OMEX Metadata, SBML, SED-ML, Open Source Brain   Pedro Fontanarrosa UCL SBOL and SBOL Visual   Prashant Vaidyanathan Oxford Biomedica SBOL and SBOL Visual, SBOL focuses on standardizing biological data to support FAIR principles, enhancing data sharing and reuse in biology. If you\u0026rsquo;re interested in learning more or contributing, let\u0026rsquo;s connect!   Rahuman Sheriff EMBL-EBI COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBML, SED-ML, PE-TAB, FROG, Stochastic Reproducibility, BioModels   Robert Vickerstaff UCL NeuroML, SBML, SED-ML   Sarah Keating UCL, London NeuroML, SBML, SED-ML, FROG, CHIMERA   Sebastian Persson University of Gothenburg SBML, PE-TAB   Sotirios Panagiotou Erasmus Medical Center, Rotterdam, NL CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SED-ML, VCell, EDEN neural simulator for NeuroML https://eden-simulator.org , BrainFrame for HPC in simulations https://neurocomputinglab.com/research-themes/brainframe/   Stela Prins UCL Multicellular modeling, NeuroML, SBML, SED-ML, Metabolic modeling, COBRA   Subhasis Ray Plaksha University, Alpha, Sector 101, IT City Rd, Sahibzada Ajit Singh Nagar, Punjab 140306 CellML, NeuroML, SBML, SED-ML, Multiscale Object Oriented Simulation Environment (https://moose.ncbs.res.in)   Swathi Anil Imperial College London, Bernstein Centre Freiburg NeuroML, Large scale network modeling to study perturbation-induced connectivity changes in the brain: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011027   T.J. Sego University of Florida Multicellular modeling, SBML, CompuCell3D, Tissue Forge   Xiaoming Hu HITS gGmbH, Schloss-Wolfsbrunnenweg 35 69118 Heidelberg Germany CellML, SBML, SED-ML, Fairdom (https://fair-dom.org/) and NFDI4Health (https://www.nfdi4health.de/en/)   Yan-Kay Ho University of Cambridge SBOL and SBOL Visual   Zainab Ashimiyu-Abdusalam EMBL-EBI, CB10, 1SD, Hinxton near Cambridge NeuroML, SBML    Attendees - remote    Name Organization Interests     Bart Jardine University of Washington CellML, COMBINE Archive, Multicellular modeling, SBML, SED-ML, OpenVT (multicell AB modeling), SBML web related tools   Carissa Bleker National Institute of Biology, Slovenia COMBINE Archive, Multicellular modeling, SBGN, SBML, SED-ML, FROG, ELIXIR Systems Biology community   Chris Evelo Maastricht University, The Netherlands BioPAX, SBGN, SBML, WikiPathways, ELIXIR\u0026rsquo;s task on PBPK modelling and SBML conversions for that   Francis Chemorion University of Pompeu Fabra, InSilicoTrials Technologies BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, PE-TAB, FROG, I am a phd student researching the management of clinical, biological and simulated data for uniform simulation workflows in the Disc4All project https://disc4all.upf.edu   Gaoxiang(Gavin) Zhou University of Pittsburgh, 4200 Fifth Ave, Pittsburgh PA 15260 BioPAX, CellML, COMBINE Archive, SBML, SBOL and SBOL Visual, PE-TAB, Dish2.0 https://github.com/pitt-miskov-zivanov-lab/ BioRECIPE https://github.com/pitt-miskov-zivanov-lab/BioRECIPE Model analysis in sensitivity etc   Haomiao Luo University of Pittsburgh BioRECIPE, CAR T cell, DiSH, BioRECIPE, http://www.nmzlab.pitt.edu   Herbert Sauro University of Washington, Seattle, USA COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML   Ilya Kiselev Biosoft.ru CellML, COMBINE Archive, Multicellular modeling, SBGN, SBML, SED-ML, BioUML platform   Jacob Beal BBN SBOL and SBOL Visual   James Glazier Indiana University, Bloomington, IN 47408 USA COMBINE Archive, Multicellular modeling, SBML, SED-ML, OpenVT (Building communities for multicell modeling), CompuCell3D multicell modeling framework (www.compucell3d.org)   John Hancock University of Ljubljana COMBINE Archive, SBML, SED-ML, FROG, ELIXIR Systems Biology Community   Leonie Lorenz EMBL-EBI SBML, SED-ML, PE-TAB, Pathogen transmission and evolution models   Lokesh V Indian Institute of Technology, Bombay SBML, FROG, I generate high quality genome scale metabolic models for industrial microorganisms. I understand the basic science of the metabolism using models and provide insilico predictions for engineering applications.   Luisa Zapata Saldarriaga Universidad de Antioquia BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, PE-TAB, FROG   Lutz Brusch Technische Universität Dresden, Dresden, Germany COMBINE Archive, Multicellular modeling, SBML, PE-TAB, MorpheusML (https://morpheus.gitlab.io/model/published-models/), SBML-Spatial, FAIRSPACE, https://www.MultiCellML.org   Matthias König Humboldt-University Berlin, Faculty of Life Science, Institute for Theoretical Biology, Berlin, Germany COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG   Nguyen Tung EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK BioPAX, CellML, COMBINE Archive, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG, BioModels: https://www.ebi.ac.uk/biomodels/   Nicholas Owen UCL Multicellular modeling, SBML, SBOL and SBOL Visual, Data Stewardship at UCL   Paola Dr Di Maio IGDORE BioPAX, CellML, COMBINE Archive, Multicellular modeling, NeuroML, SED-ML, Model Cards ML, Neuroscience Model Cards   Qi Wu HITS    Randy Heiland Indiana University, Bloomington, IN USA CellML, Multicellular modeling, SED-ML, PhysiCell, CompuCell3D   Thomas Gorochowski University of Bristol SBOL and SBOL Visual   Veronica Henao Universidad de Antioquia COMBINE Archive, NeuroML    Last updated 4 April 2024\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"90f9dc804befc661a29152dbcfcff2f7","permalink":"/author/harmony-2024/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2024/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2024","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2025 was held at KU Leuven, Leuven, Belgium, 15-18 April 2025.\nThe local organizers were Liesbet Geris, Luiz Ladeira, and Bernard Staumont.\nSister Meetings 9th Disease Maps Community Meeting - DMCM2025\nSimultaneously from 15th to 17th April 2025 at the same venue.\nThe 2025 edition of the Disease Maps Community Meeting took take place in Leuven, Belgium. This annual gathering brings together the researchers, clinicians, and domain experts involved in mapping and modelling disease mechanisms. The meeting provides a forum for exchanging best practices, sharing information, and developing tools to advance the use of systems medicine in translational medicine projects and decision making support. Building on the success of previous editions in locations like Belval, Maastricht, Sevilla, and Paris, the 2025 meeting in Leuven is attracted a diverse group of participants dedicated to furthering the understanding and application of disease maps in research and healthcare.\nThe DMCM2025 was held simultaneously with HARMONY 2025, in the same venue. This enhanced interaction between the COMBINE and the Disease Maps communities, fostering collaboration opportunities and networking. Coffee breaks and meals were shared between both meetings.\nMore information can be found here: DMCM2025.\nbyteMAL'25\nMonday 14th April 2025\nByteMAL is a conference created by and for early-career researchers in the fields of bioinformatics and systems biomedicine and aims to provide a networking platform for knowledge and expertise exchange across borders. Aiming to vitalize communication amongst researchers from The Netherlands, Belgium, and Germany, ByteMAL has been hosted alternately by the Universities of Maastricht, Aachen, and Liege and for the first time it comes to Leuven! More information will be announced soon.\nSchedule The schedule is available below. People who have attended HARMONY in the past will know that this is inclined to change as participants make their own arrangements for conversations/discussions. A link to the editable version will be sent to the mailing list.\nSchedule \nAbstract book \nBreak out booklet\nRegistration [online only, in person closed] Registration for the meeting is free. Please register at the link above as soon as possible. This will help us plan the schedule and match your interests to the timing of the breakouts, etc. Note, only registered attendees will be sent information related to the meeting.\nRegister here. Registrations for in person participation are closed. Please use the link to register for online participation.\nCall for Breakout Sessions and Tutorials All attendees can suggest breakout sessions for hacking and/or detailed discussions of certain aspects of one or several of the COMBINE standard(s), metadata and semantic annotations (format-specific or overarching), application and implementations of the COMBINE standards, or any other topic relevant for the COMBINE community. The topics for those breakout sessions, and the time slots which would suit their communities can be submitted via the link above. Note, breakout session organizers will be responsible for creating and hosting their own online sessions, if required.\nSubmit your breakout session and tutorial proposal here.\nCall for Lightning Talks and Posters Requests for a lightning talk (5 min max.) and/or poster can be submitted via the link above. Please use several forms if you want to submit abstracts on different topics. The submission deadline is outlined above. Talks will take place during the community session and posters will be displayed throughout the meeting.\nSubmit your lightning talks and posters here\nTopics of Interest  Data exchange, pipelines and model standards for systems and synthetic biology Visualization and graphical notation standards for systems and synthetic biology Standards for sharing and analyzing biological pathway data Standards for computational biological models and modelling support Metadata description and model annotation in COMBINE standard formats Implementation of COMBINE standards in tools, databases and other resources Integrated model and data management for systems and synthetic biology Standardization of Artificial Intelligence approaches in biological modelling Emerging standardization needs and multicellular modeling Community aspects of COMBINE  Workshop Location HARMONY 2025 will be held at KU Leuven - Katholieke Universiteit Leuven Ghb - Onderwijs en Navorsing 2 ON2 Herestraat 49\n3000 Leuven - Belgium\nBuilding number: 402-18\n Arrival and Transportation From Brussels-Zaventem Airport (BRU) you can take a train at the airport station to Leuven Central Station and then a bus at the bus station in front of the train station. The R90 should take around 14min to arrive at the Leuven Gasthuisberg Campus stop, just in front of the venue.\nFrom Brussels South-Charleroi Airport (CRL) you can take a bus, taxi or shuttle to Charleroi Central train station and take a train to Leuven from there. Shuttles to Midi (Zuid) station in Brussels and then a train to Leuven from there is also an option.\nLeuven is a very cyclable city. If you come by train or car you can bring your bike and enjoy the beautiful city!\nAccommodations and meals Hotel Mille Colonnes\nMartelarenplein 5, 3000 Leuven, Belgium In front of the train station, easy access to the bus station. Distance to the conference venue: 14 min by bus, 14 min by bike, 45 min walking.\nibis Leuven Centrum\nBrusselsestraat 52, 3000 Leuven, Belgium At the core of the city center, easy access to bus stops. Distance to the conference venue: 13 min by bus. 9 min by bike. 28 min walking.\nOther accommodations options can be found on Booking.com and Airbnb (specially if you want to stay closer to the venue).\nTea and coffee will be freely available throughout the meeting. In view of the number of people using the building, it may be advisable to bring your own mug!\nA sandwich lunch will also be provided - please make sure you give us the correct information as to which days you will be in attendance and any dietary requirements when you fill in the registration form.\nPower outlet E-type plugs are used in Belgium.\nSupport Interested in sponsoring our meeting? Please contact Luiz Ladeira for details.\nAttendees - in person    Name Organization Interests     Lorenzo Veschini King\u0026rsquo;s College London, Indiana University Bloomington COMBINE Archive, Multicellular modeling; Building Immune Digital Twins   Anna Niarakis University of Toulouse, MCD-CBI, CNRS COMBINE Archive, Multicellular modeling, SBML, SED-ML, SBML QUAL; Building Immune Digital Twins; CoLoMoTo   Matthias König Humboldt-University Berlin, Systems Medicine of the Liver COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG; SBML4Humans, libroadrunner   Carissa Bleker National Institute of Biology COMBINE Archive, SBGN, SBML, SED-ML, SBML-qual; https://nib-si.github.io/BoolDog/   Alan Garny University of Auckland CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SED-ML; libCellML, libOpenCOR, and OpenCOR   Frank T. Bergmann BioQUANT / Heidelberg University COMBINE Archive, SBML, SED-ML, PE-TAB, FROG; COPASI (https://copasi.org), basico (http://basico.readthedocs.io), libsbml   Te Chen Novo Nordisk Foundation Center for Biosustainability CellML, SBML   Rahuman Sheriff European Bioinformatics Institute (EMBL-EBI) CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG; EFECT stocastic simulation reproducibility   T.J. Sego University of Florida Multicellular modeling, SBML, SED-ML, PE-TAB   Charl Linssen Jülich Supercomputing Centre; RWTH Aachen CellML, NeuroML, SBML, SED-ML; NESTML domain-specific modeling language and code generator - https://nestml.readthedocs.org/ ; Automatic analysis and solver generation for dynamical systems simulation - https://ode-toolbox.readthedocs.org/   Brett Olivier Vrije Universiteit Amsterdam COMBINE Archive, SBML, SED-ML, FROG   Alessio Gamba University of Liege BioPAX, CellML, SBGN, SBML; ONTOX project. Information about the project available at https://ontox-project.eu/project/   Hugh Sorby Auckland Bioengineering Institute CellML, COMBINE Archive, SBML, SED-ML   David Nickerson Auckland Bioengineering Institute, University of Auckland CellML, COMBINE Archive, Multicellular modeling, OMEX Metadata, SED-ML, PE-TAB, Repositories, publishing; Center for Reproducible Biomedical Modeling; Physiome / Virtual Physiological Human; Physiome Model Repository; SPARC   Nguyen Tung EMBL-EBI COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, FROG; BioModels is a repository of mathematical models of biological and biomedical systems. It hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats. http://biomodels.org   Tomas Kulhanek VITO CellML, SBML; Physiolibrary, Pharmacolibrary, https://www.physiolibrary.org   Crawley Francis P. Committee on Data (CODATA), International Science Council (ISC) CellML, NeuroML, OMEX Metadata; Engaged with the EU-funded \u0026lsquo;Developing an advanced and secure environment for data visitation across the RDA (DV4RDA) as part of the EOSC-Future/RDA Artificial Intelligence and Data Visitation Working Group.   Chris Myers University of Colorado Boulder SBML, SBOL and SBOL Visual, SED-ML; iBioSim, SynBioHub, and SynBioSuite   Jacob Barhak Jacob Barhak Analytics SBML; The Reference Model for Disease Progression: https://simtk.org/projects/therefmodel and ClinicalUnitMapping.com: https://clinicalunitmapping.com/about   Thomas Schueler German Federal Institute for Risk Assessment COMBINE Archive, OMEX Metadata, SBML, SED-ML; FSKX - FAIR Scientific Knowledge Exchange Format: standardized file format designed to facilitate the efficient sharing of scientific models and datasets (https://foodrisklabs.bfr.bund.de/fskx-food-safety-knowledge-exchange-format/); RAKIP-Initiative   Martin Golebiewski HITS gGmbH COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, ISO standards, health metadata standards; ISO/TC 276 Biotechnology; European Virtual Human Twin (EDITH); National Research Data Infrastructure for Personal Health Data (NFDI4Health)   Loïc Comeliau University of Liège Multicellular modeling, SBML    Attendees - remote    Name Organization Interests     Lutz Brusch Technische Universität Dresden OpenVT, MorpheusML, MultiCellML, SBML-spatial, PEtab-MS; Multicellular modeling, https://MultiCellML.org, MorpheusML, https://morpheus.gitlab.io, PEtab-MS, https://gitlab.com/fitmulticell/fit   Ilya Kiselev Biosoft.RU COMBINE Archive, Multicellular modeling, SBGN, SBML, SBOL and SBOL Visual, SED-ML; BioUML platform (https://www.biouml.org)   Luna Li University of Washington COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML, FROG; Working at the Center for Reproducible Biomedical Modeling on standardizing and annotating models   Adel Heydarabadipour University of Washington SBGN, SBML; Model Visualization   Lucian Smith University of Washington COMBINE Archive, Multicellular modeling, OMEX Metadata, SBML, SED-ML, FROG; I work with the Center for Reproducible Biomomedical Modeling (https://reproduciblebiomodels.org/), particularly working on Tellurium, Roadrunner, and Antimony   Arnau Montagud Institute for Integrative Systems Biology (I2SysBio), CSIC-UV CellML, COMBINE Archive, Multicellular modeling, SBML, SED-ML; EDITH, PerMedCoE   Rupert Overall Humboldt University of Berlin SBGN   Prashant Vaidyanathan Oxford Biomedica SBOL and SBOL Visual   Loïc Paulevé CNRS/LaBRI, Bordeaux, France COMBINE Archive, SED-ML; CoLoMoTo software distribution - https://colomoto.github.io/colomoto-docker/   Claudine Chaouiya I2M, Aix Marseille University SBML, SED-ML; CoLoMoTo, GINsim   Sylvain Soliman Inria SBML, SED-ML   Michael Blinov UConn Health BioPAX, COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML; http://vcell.org; https://vcell.org/webstart/VCell_Tutorials/VCell_Help/topics/ch_7/DatabaseSources/VCellDatabase.html; http://bnglviz.github.io; http://MolClustpy.github.io; http://SpringSaLaDpy.github.io   Goksel Misirli Keele University Multicellular modeling, OMEX Metadata, SBML, SBOL and SBOL Visual   Metehan Unal Keele University SBOL and SBOL Visual; I am a postdoctoral research associate at the School of Computer Science and Mathematics of Keele University. I am working on a BBSRC-funded project to create, visualise and validate biological designs.   Felipe Xavier Buson University of Bristol SBOL and SBOL Visual   Fengkai Zhang NIH, US COMBINE Archive, Multicellular modeling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB   May Elebeoba University of Wisconsin-Madison Multicellular modeling, SBML, SBOL and SBOL Visual, SED-ML   Charalampos Katselis None BioPAX, CellML, COMBINE Archive, Multicellular modeling, SBML, SED-ML   John Gennari University of Washington BioPAX, CellML, COMBINE Archive, OMEX Metadata, SBML, SED-ML   Bhavyahshree Navaneetha Krishnan University of Washington BioPAX, CellML, Multicellular modeling, SBML, SED-ML    ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"6924b67086d8d868e8e02187ea815c22","permalink":"/author/harmony-2025/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2025/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2025","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2025 will be held at KU Leuven\nLocal organizers are Liesbet Geris, Luiz Ladeira, and Bernard Staumont.\nSchedule The schedule is available below. People who have attended HARMONY in the past will know that this is inclined to change as participants make their own arrangements for conversations/discussions. A link to the editable version will be sent to the mailing list.\nSchedule \nAbstract book \nBreak out booklet\nRegistration Registration for the meeting is free. Please register at the link above as soon as possible. This will help us plan the schedule and match your interests to the timing of the breakouts, etc. Note, only registered attendees will be sent information related to the meeting.\nRegister here. Registrations for in person participation are closed. Please use the link to register for online participation.\nCall for Breakout Sessions and Tutorials All attendees can suggest breakout sessions for hacking and/or detailed discussions of certain aspects of one or several of the COMBINE standard(s), metadata and semantic annotations (format-specific or overarching), application and implementations of the COMBINE standards, or any other topic relevant for the COMBINE community. The topics for those breakout sessions, and the time slots which would suit their communities can be submitted via the link above. Note, breakout session organizers will be responsible for creating and hosting their own online sessions, if required.\nSubmit your breakout session and tutorial proposal here.\nCall for Lightning Talks and Posters Requests for a lightning talk (5 min max.) and/or poster can be submitted via the link above. Please use several forms if you want to submit abstracts on different topics. The submission deadline is outlined above. Talks will take place during the community session and posters will be displayed throughout the meeting.\nSubmit your lightning talks and posters here\nTopics of Interest  Data exchange, pipelines and model standards for systems and synthetic biology Visualization and graphical notation standards for systems and synthetic biology Standards for sharing and analyzing biological pathway data Standards for computational biological models and modelling support Metadata description and model annotation in COMBINE standard formats Implementation of COMBINE standards in tools, databases and other resources Integrated model and data management for systems and synthetic biology Standardization of Artificial Intelligence approaches in biological modelling Emerging standardization needs and multicellular modeling Community aspects of COMBINE  Workshop Location HARMONY 2025 will be held at KU Leuven - Katholieke Universiteit Leuven Ghb - Onderwijs en Navorsing 2 ON2 Herestraat 49\n3000 Leuven - Belgium\nBuilding number: 402-18\n Arrival and Transportation From Brussels-Zaventem Airport (BRU) you can take a train at the airport station to Leuven Central Station and then a bus at the bus station in front of the train station. The R90 should take around 14min to arrive at the Leuven Gasthuisberg Campus stop, just in front of the venue.\nFrom Brussels South-Charleroi Airport (CRL) you can take a bus, taxi or shuttle to Charleroi Central train station and take a train to Leuven from there. Shuttles to Midi (Zuid) station in Brussels and then a train to Leuven from there is also an option.\nLeuven is a very cyclable city. If you come by train or car you can bring your bike and enjoy the beautiful city!\nSister Meetings 9th Disease Maps Community Meeting - DMCM2025\nSimultaneously from 15th to 17th April 2025 at the same venue.\nThe 2025 edition of the Disease Maps Community Meeting is set to take place in Leuven, Belgium. This annual gathering brings together the researchers, clinicians, and domain experts involved in mapping and modelling disease mechanisms. The meeting provides a forum for exchanging best practices, sharing information, and developing tools to advance the use of systems medicine in translational medicine projects and decision making support. Building on the success of previous editions in locations like Belval, Maastricht, Sevilla, and Paris, the 2025 meeting in Leuven is expected to attract a diverse group of participants dedicated to furthering the understanding and application of disease maps in research and healthcare.\nThe DMCM2025 will be held simultaneously with HARMONY 2025, in the same venue. This is expected to enhance interaction between the COMBINE and the Disease Maps communities, fostering collaboration opportunities and networking. Coffee breaks and meals will be shared between both meetings.\nMore information can be found here: DMCM2025.\nTo have access to the DMCM talks, registrations should be done separately.\nbyteMAL'25\nMonday 14th April 2025\nByteMAL is a conference created by and for early-career researchers in the fields of bioinformatics and systems biomedicine and aims to provide a networking platform for knowledge and expertise exchange across borders. Aiming to vitalize communication amongst researchers from The Netherlands, Belgium, and Germany, ByteMAL has been hosted alternately by the Universities of Maastricht, Aachen, and Liege and for the first time it comes to Leuven! More information will be announced soon.\nAccommodations and meals Hotel Mille Colonnes\nMartelarenplein 5, 3000 Leuven, Belgium In front of the train station, easy access to the bus station. Distance to the conference venue: 14 min by bus, 14 min by bike, 45 min walking.\nibis Leuven Centrum\nBrusselsestraat 52, 3000 Leuven, Belgium At the core of the city center, easy access to bus stops. Distance to the conference venue: 13 min by bus. 9 min by bike. 28 min walking.\nOther accommodations options can be found on Booking.com and Airbnb (specially if you want to stay closer to the venue).\nTea and coffee will be freely available throughout the meeting. In view of the number of people using the building, it may be advisable to bring your own mug!\nA sandwich lunch will also be provided - please make sure you give us the correct information as to which days you will be in attendance and any dietary requirements when you fill in the registration form.\nPower outlet E-type plugs are used in Belgium.\nSupport Interested in sponsoring our meeting? Please contact Luiz Ladeira for details.\n","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"41a3dc14847cbc80a6267e100c8f136f","permalink":"/author/harmony-2025/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2025/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2025","type":"authors"},{"authors":null,"categories":null,"content":" The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure. There are generally not many general discussions or oral presentations during HARMONY; instead, the time is devoted to allowing hands-on hacking and interaction between people focused on practical development of software and standards.\nHARMONY 2026 was held at the University of Auckland.\nLocal organizers are David Nickerson, Weiwei Ai, Jarrah Dowrick, Alan Garny, and Hugh Sorby at the Auckland Bioengineering Institute.\nAuckland Human Digital Twin Meetings 2026 From 2–12 Feb 2026, the Auckland Bioengineering Institute hosts three workshops in Auckland advancing digital twin modelling, interoperability standards, and clinical translation.\nOn this page you can find conference accommodation rates, venue and transport information for getting around Auckland, details on the other workshops happening during the same period, information about Waitangi Day — New Zealand’s national holiday, which falls during the meetings; as well as an optional Waiheke Island excursion and plenty of things to do and places to dine around the city.\nWorkshop Location HARMONY 2026 was held at the University of Auckland. It will be co-located with the 2026 Cardiopulmonary Physiome Workshop.\nThe workshop took place at:\nThe Faculty of Engineering (Building 401) Atrium (Room 418) 20 Symonds Street, Auckland Central.\nCurrent Schedule Arrival and Transportation Getting from Auckland Airport (AKL) to the central city (also known as the \u0026lsquo;CBD\u0026rsquo;) is straightforward. Your main options depend on your budget, time, and preference for convenience.\nQuick Comparison Table    Method Approx. Cost (1 Adult) Approx. Time Best For     Public Transport ~$6.50 50 - 60 mins Budget   Express Bus (SkyDrive) ~$18 35 - 50 mins Simplicity \u0026amp; Value   Ride-Share (Uber) ~$40 - $65 25 - 45 mins On-Demand Convenience   Taxi (Fixed Fare) ~$62 - $99 20 - 40 mins Speed \u0026amp; Ease   Shared Shuttle ~$25 - $40 45 - 75 mins Door-to-Door Value    Note: Travel times can be heavily affected by traffic, especially during morning (7:00 AM - 9:30 AM) and evening (4:00 PM - 6:30 PM) peak hours.\n Visitor Tip: Always ask for a fixed fare or flat rate to the city before you get in. Metered fares can be much more expensive (up to $90-$100+ in bad traffic).\n Further information on these transport options is available in the following places:\n Public Transport Express Bus (SkyDrive) Ride-Sharing (Uber) Taxi (Fixed Fare) Shared Shuttle  Accommodation Accommodation has been combined with the Human Digital Twin meetings and information on accommodation can be found there.\nHuman Digital Twin meetings accommodation information\nMeals Meals during the day for Harmony 2026 will be provided in coordination with the other digital twins meetings. For evening meals there is a great selection of a wide variety of restaurants a short walk or short taxi/Uber from the conference location.\nPower outlet Type I plugs are used in New Zealand, featuring three flat pins arranged in a triangular pattern. They operate on a voltage of 230V and are designed to ensure safety with an earth pin for grounding.\nPlugs used in New Zealand (Wikipedia).\nAttendees The following are the registered attendees for HARMONY 2026, as of 2026-01-29 01:28 UTC.\n   Name Affiliation Attendance Interests     Hugh Sorby Auckland Bioengineering Institute In person CellML, SED-ML   Falk Schreiber University of Konstanz In person SBGN, SBML, SBOL and SBOL Visual   Alan Garny University of Auckland In person CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SED-ML   Weiwei Ai Auckland Bioengineering Institute, University Of Auckland In person CellML, SED-ML, PE-TAB   Xiaoming Hu Bioquant, University Heidelberg In person SBML, Data Management, Ro-Crate   Lucian Smith University of Washington In person COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBML, SED-ML, FROG   Chris Myers University of Colorado Boulder In person COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML   Frank T. Bergmann BioQUANT, Heidelberg University In person COMBINE Archive, SBGN, SBML, SED-ML, PE-TAB, FROG   David Nickerson Auckland Bioengineering Institute, University of Auckland In person CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SED-ML, PE-TAB, repositories; model publishing   Eric Young WPI In person SBOL and SBOL Visual   Triana Karnadipa ABI Remotely COMBINE Archive, NeuroML, OMEX Metadata   Pedro T. Monteiro IST - University of Lisbon Remotely Multicellular Modelling, SBML, SED-ML, FROG   MORETTI Sébastien SIB Swiss Institute of Bioinformatics Remotely BioPAX, SBGN, SBML   Ayesha Abubakr St. John\u0026rsquo;s Kilmarnock School Remotely BioPAX, CellML, Multicellular Modelling, NeuroML, SBML, SBOL and SBOL Visual, SED-ML   Gonzalo Vidal University of Colorado Boulder Remotely SBOL and SBOL Visual   Hoda Rahimi The University of Auckland Remotely BioPAX, CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB   Litian Su Auckland Bioengineering Institute Remotely CellML, SBML   Maria Chiara Langella University of Naples Federico II Remotely BioPAX, CellML, COMBINE Archive, Multicellular Modelling, SBML, SBOL and SBOL Visual, PE-TAB   Leo Willyanto Santoso Auckland Bioengineering Institute, The University of Auckland Remotely CellML   Koray Atalag Auckland Bioengineering Institute Remotely health data interoperability (FHIR, openEHR, SNOMED, LOINC, ICD etc.)   Lutz Brusch TU Dresden, Germany Remotely Multicellular Modelling, SBML, PE-TAB, OpenVT, MultiCellML, MorpheusML   Jarrah Dowrick Auckland Bioengineering Institute In person CellML, COMBINE Archive, OMEX Metadata, SBGN, SED-ML, FieldML   Goksel Misirli Keele University Remotely Multicellular Modelling, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual    University at Buffalo Remotely    Marc Molla Garcia UPF In person BioPAX, CellML, COMBINE Archive, Multicellular Modelling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, PE-TAB, FROG   Matthias König Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Biology, Institute of Theoretical Biology, Systems Medicine of the Liver; University of Stuttgart, Institute of Structural Mechanics and Dynamics in Aerospace Engineering Remotely CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG   Augustin Luna National Library of Medicine Remotely BioPAX, SBGN   Hasan Balci National Library of Medicine, NIH Remotely SBGN, SBML   Fengkai Zhang NIH, US Remotely COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBOL and SBOL Visual, SED-ML, PE-TAB   Te Chen Technical University of Denmark Remotely SBML, SED-ML   Viola Rintoul UW Madison Remotely CellML, COMBINE Archive, Multicellular Modelling, SBOL and SBOL Visual, SED-ML   Rahuman Sheriff EMBL-EBI Remotely CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG    ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"1cb07af65563c04b72aa85b4693e257b","permalink":"/author/harmony-2026/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2026/","section":"authors","summary":"The \u0026ldquo;Computational Modeling in Biology\u0026rdquo; Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. HARMONY is a codefest-type meeting, with a focus on development of the standards, interoperability and infrastructure.","tags":null,"title":"HARMONY 2026","type":"authors"},{"authors":["HUPO-PSI"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"46bec7b12de991e8152813009b35359e","permalink":"/author/hupo-psi/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/hupo-psi/","section":"authors","summary":"","tags":null,"title":"HUPO-PSI","type":"authors"},{"authors":["Identifiers.org"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"038100718f010d33abb8bb827c9a386c","permalink":"/author/identifiers.org/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/identifiers.org/","section":"authors","summary":"","tags":null,"title":"Identifiers.org","type":"authors"},{"authors":["KiSAO"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"0658e80816b78392594dae48922a75d9","permalink":"/author/kisao/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/kisao/","section":"authors","summary":"","tags":null,"title":"KiSAO","type":"authors"},{"authors":["MAMO"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"128f497ea3253df16cb379e8dae23d45","permalink":"/author/mamo/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/mamo/","section":"authors","summary":"","tags":null,"title":"MAMO","type":"authors"},{"authors":["Martin Golebiewski"],"categories":null,"content":"Martin Golebiewski (Biochemist) works at HITS, a private non-profit institute in Heidelberg (Germany). His main interests are data management and integration for systems biology. He chairs the \u0026lsquo;data processing and integration\u0026rsquo; working group of the ISO technical committee for biotechnology (ISO/TC 276) and co-leads the work package for “Data sources and standards for predictions in personalized medicine” of the European project EU-STANDS4PM. He is involved as data manager in the German Liver Systems Medicine network LiSyM and associated with the data management infrastructure FAIRDOM. Previously, he has coordinated the NormSys project and was involved in the reaction kinetics database SABIO-RK, as well as in the Infrastructure for Systems Biology Europe (ISBE).\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"4e53d48e8a3b0d9f8d41a5772fcca786","permalink":"/author/martin-golebiewski/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/martin-golebiewski/","section":"authors","summary":"Martin Golebiewski (Biochemist) works at HITS, a private non-profit institute in Heidelberg (Germany). His main interests are data management and integration for systems biology. He chairs the \u0026lsquo;data processing and integration\u0026rsquo; working group of the ISO technical committee for biotechnology (ISO/TC 276) and co-leads the work package for “Data sources and standards for predictions in personalized medicine” of the European project EU-STANDS4PM.","tags":null,"title":"Martin Golebiewski","type":"authors"},{"authors":["Matthias Koenig"],"categories":null,"content":" Matthias König (PhD in Biophysics) is Head of the Systems Medicine of the Liver Lab at Humboldt-Universität zu Berlin, Faculty of Life Sciences, Institute of Biology (ITB), and Head of the Computational Biomechanics Group at the University of Stuttgart, Institute of Structural Mechanics and Dynamics in Aerospace Engineering.  His research focuses on computational modeling, data science, bioinformatics, and machine learning applied to biological, medical, and clinical data, with a particular emphasis on predictive and mechanistic models of liver function, physiology, and drug metabolism.  He has been actively involved in the development of community standards and tools in systems and computational biology, including SBML, SED-ML, and software supporting these standards, as well as the COMBINE initiative and the COMBINE Archive. His work strongly emphasizes reproducibility, interoperability, and FAIR data and modeling practices.  More information about his research is available at https://livermetabolism.com  ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"8f115c37dbfaa3f52c1014cec977368e","permalink":"/author/matthias-konig/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/matthias-konig/","section":"authors","summary":"Matthias König (PhD in Biophysics) is Head of the Systems Medicine of the Liver Lab at Humboldt-Universität zu Berlin, Faculty of Life Sciences, Institute of Biology (ITB), and Head of the Computational Biomechanics Group at the University of Stuttgart, Institute of Structural Mechanics and Dynamics in Aerospace Engineering.","tags":null,"title":"Matthias König","type":"authors"},{"authors":["MIRIAM"],"categories":null,"content":"The Minimal Information Required In the Annotation of Models, initiated by the BioModels.org effort, aimed to produce a set of guidelines for the consistent annotation and curation of computational models in biology. It is suitable for use with any structured format for computational models.\nMIRIAM is a registered project of MIBBI (Minimum Information for Biological and Biomedical Investigations).\nMIRIAM guidelines MIRIAM guidelines are composed of three parts: #Reference correspondence, #Attribution annotation, and #External resource annotation. These are described below:\nMIRIAM guidelines components Reference correspondence  The model must be encoded in a public, standardized, machine-readable format (SBML, CellML, GENESIS, \u0026hellip;). The model must comply with the standard in which it is encoded. The model must be clearly related to a single reference description. If a model is composed of different parts, it should still be accompanied with a description of the derived/combined model. The encoded model structure must reflect the biological processes described by the reference description. The model must be instantiable in a simulation: all quantitative attributes must be defined, including initial conditions. When instantiated, the model must be able to reproduce all results given in the reference description within an epsilon (algorithms, round-up errors).  Attribution annotation  The model has to be named. A citation to the reference description must be provided (complete citation, unique identifier, unambiguous URL). The citation should identify the authors of the model. The name and contact information for model creators must be provided. The date and time of model creation and last modification should be specified. A history is useful but not required. The model should be linked to a precise statement about the terms of it\u0026rsquo;s distribution. MIRIAM does not require “freedom of use” or “no cost”.  External resource annotation  The annotation must unambiguously relate a piece of knowledge to a model constituent. The referenced information should be described using a triplet {collection, identifier, qualifier}: The annotation should be written as a Uniform Resource Identifier (URI). The identifier should be considered within the context of the framework of the collection. Collection namespace and identifier are be combined into a single URI, such as: https://identifiers.org/collection/identifier. For example: https://identifiers.org/uniprot/P62158. Qualifiers (optional) should refine the link between the model constituent and the piece of knowledge: “has a”, “is version of”, “is homolog to”, etc. The standard set of valid URIs is agreed upon by the community. A database and the associated API (Web Services) have been developed at the EBI to provide the generation and interpretation of URIs.  MIRIAM URIs An important part of the MIRIAM guidelines consists of the controlled annotation of model components, based on Uniform Resource Identifiers (URIs). In order to support this task, a set of controlled URIs were created: MIRIAM URIs. These allowed the unique and unambiguous identification of a model component, in a stable and perennial manner. The #MIRIAM Registry and Identifiers.org system are a set of services and resources that provide support for generating, interpreting and resolving MIRIAM URIs.\nMIRIAM URIs are composed of two main parts: the first defines a namespace that particular \u0026lsquo;entities of the same type\u0026rsquo; may occupy. This is called a collection. The second component precisely identifies a given entity within this collection, called a record. For example, https://identifiers.org/pubmed/16333295 is the MIRIAM URI that identifies the publication of the MIRIAM Standard within the PubMed data collection. Here, https://identifiers.org/pubmed defines the collection (PubMed), and \u0026lsquo;16333295\u0026rsquo; precisely identifies the record within it.\nMIRIAM Registry and Identifiers.org In order to enable the interoperability of this annotation scheme, the community has to agree upon a set of recognised collections. The MIRIAM Registry is an online service created to catalogue these collections, their URIs and the corresponding physical URLs or resources, whether they are controlled vocabularies or databases.\nBy using the MIRIAM Registry, one can (via Web Services) generate MIRIAM URIs (URN form), as well as resolve them (transform them into physical locations of the corresponding pieces of knowledge). Directly resolvable URIs, are also made available through Identifiers.org, which acts as a resolving layer above the the Registry. Both forms will be supported equally, with services provided to allow interconversion between them.\nPublications Juty N., Le Novère N., Laibe C. (2012) Identifiers.org and MIRIAM Registry: community resources to provide persistent identification. Nucleic Acids Research, 40: D580-D586 PubMed - Open Access\nLaibe C., Le Novère N. (2007) MIRIAM Resources: tools to generate and resolve robust cross-references in Systems Biology. BMC Systems Biology, 1: 58 PubMed - Open Access\nLe Novère N, Courtot M, Laibe C (2007) Adding semantics in kinetics models of biochemical pathways. Proceedings of the 2nd International Symposium on experimental standard conditions of enzyme characterizations\nLe Novère N., Finney A., Hucka M., Bhalla U., Campagne F., Collado-Vides J., Crampin E., Halstead M., Klipp E., Mendes P., Nielsen P., Sauro H., Shapiro B., Snoep J.L., Spence H.D., Wanner B.L. (2005) Minimum Information Requested In the Annotation of biochemical Models (MIRIAM) Nature Biotechnology, 23: 1509-1515. PubMed - DOI\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"8fc974a0f3a7d814933abb2fc7bbed73","permalink":"/author/miriam/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/miriam/","section":"authors","summary":"The Minimal Information Required In the Annotation of Models, initiated by the BioModels.org effort, aimed to produce a set of guidelines for the consistent annotation and curation of computational models in biology.","tags":null,"title":"MIRIAM","type":"authors"},{"authors":["NeuroML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"0e2ecf7e3693609e57a9139ef1b31944","permalink":"/author/neuroml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/neuroml/","section":"authors","summary":"","tags":null,"title":"NeuroML","type":"authors"},{"authors":["NeuroML"],"categories":null,"content":"The NeuroML project focuses on the development of an XML based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models.\nThe latest stable specification is Version 2.2.\nNeuroML development is coordinated by an elected editorial board.\nMore information.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"61cbd1234d792e8969290b2388e75b58","permalink":"/author/neuroml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/neuroml/","section":"authors","summary":"The NeuroML project focuses on the development of an XML based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models.","tags":null,"title":"NeuroML","type":"authors"},{"authors":["NineML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bfb857dc2233d5fca030a97d9c3ce401","permalink":"/author/nineml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/nineml/","section":"authors","summary":"","tags":null,"title":"NineML","type":"authors"},{"authors":["NuML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"c1576c1dc6efd309523c1cd0fdec8864","permalink":"/author/numl/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/numl/","section":"authors","summary":"","tags":null,"title":"NuML","type":"authors"},{"authors":["COMBINE Archive"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"7a999c9d9d7018c0cb4e25ccc963668c","permalink":"/author/omex/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/omex/","section":"authors","summary":"","tags":null,"title":"OMEX","type":"authors"},{"authors":null,"categories":null,"content":"The coordination of COMBINE owes much to the people organizing the meetings, and in particular the hosts of the events. Conversely, COMBINE events have become such successes that hosting them boosts recognition in the field, and permits to build or to strengthen collaborations.\nPeople interested in organizing a meeting should start by filling the interest survey. This will permit to highlight the advantages and potential issues associated with each application, and start the discussion with COMBINE coordinators. More information about the organization of COMBINE meetings can be found in the detailed guidelines below.\nProcedure to organize a COMBINE meeting People interested in organizing a COMBINE meeting should begin by filling out the interest survey as early as possible. This will enable potential hosts to highlight the advantages and possible issues associated with each bid, and start the discussion with the COMBINE coordinators. The currently-planned events are listed on the COMBINE events page; dates not listed there are usually still up for bidding.\nWell in advance of a given future event, the COMBINE coordinators will discuss the bids made. Based on the qualities of the proposals, as well as more strategic considerations such as alternating timezones and proximity with other conferences, the coordinators prioritize the bids and also engage in discussions with potential hosts. When a project is mature, it is announced on the event page, as well as on Twitter, and on other social media.\nDepending on the country where the meeting is located, some people may need visas to enter the country. This can be easier or harder for people, depending on their country of origin and the hosting country. For example, Russian and Chinese nationals have a harder time getting into the USA. To make this even possible for them, they need to know the planned meeting location \u0026lsquo;\u0026lsquo;very\u0026rsquo;\u0026rsquo; far in advance, because the visa application process takes many months.\nResponsibilities of each stakeholder COMBINE coordinators   The COMBINE coordinators evaluate the bids and select potential locations for the various meetings.\n  They write letters of support for grant applications written by the bidding groups to support the event.\n  They create the master web pages and documents for the meeting on the COMBINE website.\n  Local organizers   The local organizers seek funding for the event.\n  They choose the venue for the event.\n  They organize the catering for lunch and coffee break plus a conference dinner.\n  They run the logistic of the meeting.\n  They set up the registration system. (Often they can make use of a free service such as Eventbrite.)\n  They decide how much to charge in registration fees (if any are needed).\n  They collect the registration fees and issue the receipts to attendees.\n  They act as the single point of contact with the attendees.\n  COMBINE coordinators + Local organizers   Together, the COMBINE coordinators and local organizers decide about the dates of the event.\n  Together, the COMBINE coordinators and local organizers develop the program of the event.\n  For COMBINE forums, they collaborate to select session chairs.\n  Finances The organization of COMBINE meetings can be costly, and the earlier that budgets are established, the better for everyone.\nExpenses We \u0026lsquo;\u0026lsquo;\u0026lsquo;require\u0026rsquo;\u0026rsquo;\u0026rsquo; the local organization to provide:\n  the venue, including meeting rooms, networking, etc.\n  catering for lunch and coffee break. While food and beverage are important, staffing is not. If money can be saved by having self-service rather than waiters, this option should be chosen.\n  if the venue is far from any convenient accommodation, shuttles should be provided to and from the venue.\n  In addition, we gently \u0026lsquo;\u0026lsquo;\u0026lsquo;request\u0026rsquo;\u0026rsquo;\u0026rsquo; the organizers to support a conference dinner. In exceptional cases, the cost of the conference dinner can be covered by attendees. However, this can cause problems for people who are not refunded or have per-diem refunding systems (because in the latter case, the dinner can be more expensive than what is refunded). This results in some attendees skipping the conference dinner, which is unfortunate because the dinner is always a high point of COMBINE meetings. Everyone benefits if the organizers do their best to facilite the participation.\nFor HARMONY hackathons, it is \u0026lsquo;\u0026lsquo;\u0026lsquo;advised\u0026rsquo;\u0026rsquo;\u0026rsquo; to seek free accommodation, or financial support to help with accommodation costs. The rationale is that developers are giving their time to the support of the standards, and we should ease the development of support as much as possible.\nThere is no COMBINE policy on travel costs. It is not mandatory for the organizers to refund any travel costs. It may be that travel support for attendees is requested as part of a grant application. This is fine if that helps securing funding; however, refunding travel costs should be considered after other expenses above are met.\nSimilarly, we do not impose a policy on speaker invitations. Having invited speakers at COMBINE forum may help securing funding. Note, however, that external speakers are discouraged at HARMONY hackathons, because those events should remains technical and productive events. If speakers are invited, funding for them should come after other expenses above are met. Local organizers are assumed to take responsibility for all arrangements for invited speakers (e.g., accomodations, transportation, etc.).\nIncome Funding for COMBINE events comes from different sources (e.g., funding agencies, universities, local companies). If possible, cheap or even free venues should be used. An example is rooms made available by university housing.\nFor COMBINE forums, registration fees bring a significant income. We advise a fee of roughly 25 Euros per day (30 Dollars, 20 GBP). Part of the reason for the fees is to encourage people to attend the entire conference rather than skip out early (or worse, not show at all) because it did not cost them anything to sign up. In past events, a single fee was charged for all attendees regardless of status, but some people have also requested that students pay less than non-students; this matter is still up for debate and discussion.\nFees for HARMONY hackathons are discouraged. The reason is that we want to encourage as many developers as possible to attend the hackathons, and fees discourage attendance.\nScientific organization The scientific organization of COMBINE meetings should start as early as possible. Some people need to have an idea of the program before they will register. However, drawing a detailed program early is counterproductive in that (i) some people may not see their topic of interest and decide not to register; (ii) the program will almost certainly evolve as people register and start self-organizing. It is best to open registration as early as possible, and close it a couple of weeks before the event. Late registrations can always be accommodated on a case-per-case basis, but should remain rare.\nThere are roughly four stages in preparing the program. (Note that programs for COMBINE forums need to be more detailed than those for HARMONY hackathons.) The stages are as follows:\n  As early as possible, and at least before registration begins, the local organizers and COMBINE coordinators discuss a rough program, with thematic blocks. For example, some blocks may be \u0026ldquo;model description (SBML, CellML and related standards)\u0026rdquo;, \u0026ldquo;cross-COMBINE standards\u0026rdquo;, etc. At this stage, an initial allocation of rooms to sessions should also be made.\n  As registrations accumulate, the editorial boards of the different COMBINE standards are brought into the discussion to help defining \u0026ldquo;their\u0026rdquo; sessions. Blocks are adapted following the registration trends (e.g., more \u0026ldquo;SBML people\u0026rdquo; in attendance means more time dedicated to SBML issues, etc.) and the final rooms are attributed. The blocks of topics are refined further; e.g., \u0026ldquo;SBML package X\u0026rdquo;, \u0026ldquo;SBGN language Y\u0026rdquo;, etc. In the case of COMBINE forums, chairs are nominated and approached. (In the case of HARMONY hackathons, pure hacking sessions do not need chairs.)\n  For sessions involving presentations or tutorials, the session chairs, together with the relevant editorial boards if needed, select the speakers and their order.\n  The last step is event-time reorganization; that is, changes during the event. COMBINE meetings are living meetings; new discussion topics frequently emerge during the course of the meetings and need to be accommodated in the program.\n  Poster sessions need to have some dedicated time to them, perhaps combined with extended breaks in the afternoon. Without dedicated time in the schedule, many people simply never go to look at the posters because they are busy. In the past, people did not like combining the poster session with lunch, especially if lunch required going off-site. The location of the posters also makes a difference to the success of the poster session. If they are segregated in a separate room not visible to the main meeting room, fewer people visit. The ideal situation is if the posters are right outside of the main meeting room, or even inside (if the room is big enough).\nThe registration process should also include the possibility for participants to submit abstracts for talks and posters.\nPractical considerations Venue Rooms One main room is required for plenary presentations and discussions. The main room for COMBINE forums (a meeting which features many talks) should have audio/microphone equipment, so that people in the back can hear, and we can record the sessions.\nIn addition to the main room, breakout rooms nearby are needed for ad hoc separate discussions and meetings. There needs to be an overhead projector and projection screen or surface in each room. If possible, the breakout rooms also should have whiteboards. Paper pads and pens/pencils come handy too, although it is not necessary to place one per desk/person; the materials could be left at the front of the room for those people who desire them.\nIn the past, people have expressed a dislike for having presentations in the same room as where people are attempting to hack and work. They have found that fewer than the majority were interested in the presentation of a given topic, so the result was that a greater number of people were distracted and inconvenienced. The implication is that for HARMONY, it must be possible to have presentations for (let us say) half the attendees in a separate room from the main working room.\nThe venue should not have an early closing or clear-out time. People sometimes want to work or have discussions right up to dinner time, and if the facilities forces them out by (e.g.) 6 PM, it is inconvenient. This is particularly important for COMBINE forums. If a cut-off time is unavoidable, then it must be reasonable. We absolutely cannot have a 5 PM cut-off time; that is too early.\nNetworking It is critical to have a fast and reliable network that can handle 60 people using it at the same time. \u0026lsquo;\u0026lsquo;\u0026lsquo;The capacity issue is serious.\u0026rsquo;\u0026rsquo;\u0026rsquo; Many facilities \u0026lsquo;\u0026lsquo;\u0026lsquo;claim\u0026rsquo;\u0026rsquo;\u0026rsquo; to be able to support this capacity, but when tested, turn out to be unable to handle that many \u0026lsquo;\u0026lsquo;\u0026lsquo;simultaneous\u0026rsquo;\u0026rsquo;\u0026rsquo; users. What then happens during meetings is that the network saturates and frustrates everyone in the room. \u0026lsquo;\u0026lsquo;\u0026lsquo;This has happened repeatedly, so we cannot overstate the importance of verifying that the network truly can handle the load.\u0026rsquo;\u0026rsquo;\u0026rsquo; Do not simply trust what your networking/facilities/IT people claim. You need to verify the capacity or have direct experience from past meetings in the same room.\nFor HARMONY, network access must be free to the attendees. For COMBINE forums, it is highly preferrable that access be free too, although a pay-for-access scheme would also work.\nWireless networking is preferrable. If only wired connections are available, we need to know ahead of time so that someone can bring wireless base stations for people who don\u0026rsquo;t have wired networking as an option on their computing system. Also enough access points and ethernet cables should be provided. If the facility or room already provides wireless networking, then having one or a few fast wired connections is still highly desirable, for example to be able to stream video of the sessions.\nComplex security precautions are a strong negative. Particularly annoying are systems that require you to log in via a web page every time you reconnect to the network.\nPorts should be open so that people can log to remote systems, download/upload files, etc. (For instance, ssh and sftp ports should not be blocked by the network.)\nAt some venues, a technician has to be present during meetings; the costs for this have to be taken into consideration in the meeting budget.\nElectricity Remember that virtually all COMBINE attendees are bringing laptops. They expect to run them during the meetings. (During hackathons, 100% of the people need to run their computers 100% of the time.) For this reason, \u0026lsquo;\u0026lsquo;\u0026lsquo;it is critical to have power outlets for everyone in the room\u0026rsquo;'\u0026rsquo;, distributed rationally throughout the room. Most attendees will not bring extension cords, so it is really not workable to have a room where power is available but distributed in only a few locations in the room. It is simply not viable to have a few power outlets distributed around the periphery of the room (which is, sadly, all too common).\nFlexible table/chair arrangements HARMONY requires desks, preferably movable desks and chairs. COMBINE forums are also best served with movable desks and chairs, but lecture halls have also worked in the past. (However, if it is a lecture hall arrangement, then there must be power outlets near every seat so that people can still set up their laptops.)\nOthers Prepare name badges and relevant information (network access, local map, printed program) for participants. Give a welcome address and let participants know where they can find help (e.g., local oranizers).\nWhat to avoid   Lecture-hall seating arrangement with very tight spacing. If one can only get in and out of the rows from the sides, people cannot get in or out of the middle seats without requiring all people in the intervening seats to get up and let them through.\n  Desktops attached to the rows in front of each seat with a fold-away arrangement with a gap that can cause contents such as laptops to be easily spilled on the floor.\n  Accommodation Hotels Sometimes hotels agree on special rates for events which can be helpful to reduce the costs for participants. A list of appropriate hotels should be put on the web by the local organizers.\nA range of hotels should ideally be within walking distance of the venue. Note that because of physical disabilities, some people will require taxis or other mode of transportation for anything over 1 city block, even if the hotels are in walking distance for most other people. For this reason, the option of taxi transportation must also exist. (In other words, it is a deal-breaker to be in a location where venue and hotels are separate and the only available mode of travel between the two is walking. It is impossible for some attendees to do this.)\nChartered bus transportation should be avoided if possible. In general, any mode of transportation that requires people to come and go at only a couple of specific times during the day is suboptimal. Public transportation is acceptable but people want to be able to come and go on their schedule, not someone else\u0026rsquo;s. So, walking, subways, regular trains, regular buses (as in a city), etc., are all okay from that respect.\nJust like at the meeting venue, it is critical that the hotel(s) haves fast and reliable networking. People work in their rooms before and after the meetings!\nAthletic facilities available is a plus, either at the hotels or nearby. For a one-week stay, it becomes a consideration for people. This is more than simply the option of running outside. Some people may not be able to run due to physical reasons, but can use cardio equipment in a gym; moreover, weight training equipment is important to some people.\nAirport transportation issues It is vastly preferable if people can arrange their own reasonably-priced transportation from the airport to the hotels. The alternative of having to arrange transportation (either individual cars or vans) not only tends to be expensive for the organizers or hosts, but also is incredibly complicated to arrange. (It requires knowing everyone\u0026rsquo;s flight schedules, AND it requires the organizers to be responsible for dealing with the situation where someone\u0026rsquo;s flight is delayed or cancelled, to avoid stranding that person at the airport.)\nCatering Coffee/tea/soft drinks/water needs to be available nearby. Coffee and tea is not enough; some people don\u0026rsquo;t drink either and really want soft drinks or water.\nThe location is best right outside the room. It is especially best to avoid having to go to another building altogether, for reasons of time, inconvenience, and possibly weather complications.\nFood/snacks are desirable to go along with the beverages.\nIf there are many restaurants and stores within walking distance of the hotels, not all meals have to be arranged by the organizers. Conversely, if the attendees are essentially trapped, then the organizers must arrange all meals. Note that the latter represents significantly more work and a higher cost to the organizers.\nAt least one group dinner should be arranged by the organizers or hosts. This will require having a restaurant or catering option that can handle groups of 50–90 people.\nExperience showed that fixed menus are preferable to prearranged dinners in which people have to choose from fixed menus earlier in the day, with the expectation that the restaurant will have the meals ready when they get there. People not only forget what they had ordered; they also tend to change their minds. If the aim is to feed a lot of people with choice, it is preferable to find a buffet.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"a6b010dc4c9c29126711871806d6f65e","permalink":"/author/organizing-a-combine-event/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/organizing-a-combine-event/","section":"authors","summary":"The coordination of COMBINE owes much to the people organizing the meetings, and in particular the hosts of the events. Conversely, COMBINE events have become such successes that hosting them boosts recognition in the field, and permits to build or to strengthen collaborations.","tags":null,"title":"Organizing a COMBINE event","type":"authors"},{"authors":["Padraig Gleeson"],"categories":null,"content":"Padraig Gleeson is a Principal Research Fellow at University College London. His work focuses on development of tools and standards to facilitate the generation, analysis and sharing of models of biologically detailed neuronal networks. He has developed neuroConstruct, a graphical application for constructing and analysing such models in 3D. He is the main technical contributor to the NeuroML language for simulator independent model descriptions in neuroscience. He leads the development of the Open Source Brain repository which aims to facilitate the sharing and collaborative development of neuronal models in an open source environment. He is also a Senior Contributor to the OpenWorm project which is seeking to create a highly detailed in-silico model of the nematode C. elegans.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2b330f4676eb4672120d6831941b636b","permalink":"/author/padraig-gleeson/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/padraig-gleeson/","section":"authors","summary":"Padraig Gleeson is a Principal Research Fellow at University College London. His work focuses on development of tools and standards to facilitate the generation, analysis and sharing of models of biologically detailed neuronal networks.","tags":null,"title":"Padraig Gleeson","type":"authors"},{"authors":["PEtab"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"421db2a20f03f37cd45601bad337201e","permalink":"/author/petab/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/petab/","section":"authors","summary":"","tags":null,"title":"PEtab","type":"authors"},{"authors":["SBGN"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"18c5fcfef0fcdc0e8171defcb0472a84","permalink":"/author/sbgn/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbgn/","section":"authors","summary":"","tags":null,"title":"SBGN","type":"authors"},{"authors":["SBGN"],"categories":null,"content":"The Systems Biology Graphical Notation (SBGN), is a set standard graphical languages to describe visually biological knowledge. It is currently made up of three languages describing Process Descriptions, Entity Relationships and Activity Flows.\nThe last specifications are SBGN PD Level 1 Version 2.0, SBGN ER Level 1 Version 2 and SBGN AF Level 1 Version 1.2.\nSBGN development is coordinated by an elected editorial board and a Scientific Committee.\nSeveral data resources and software claim support for SBGN. An API is available to help implementing support: libSBGN\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"105662dc20077cd98f7788fdc1b5b527","permalink":"/author/sbgn/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbgn/","section":"authors","summary":"The Systems Biology Graphical Notation (SBGN), is a set standard graphical languages to describe visually biological knowledge. It is currently made up of three languages describing Process Descriptions, Entity Relationships and Activity Flows.","tags":null,"title":"SBGN","type":"authors"},{"authors":["SBML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2f66706314300300d75bf838913c662d","permalink":"/author/sbml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbml/","section":"authors","summary":"","tags":null,"title":"SBML","type":"authors"},{"authors":["SBML"],"categories":null,"content":"The Systems Biology Markup Language (SBML) is a computer-readable XML format for representing models of biological processes. SBML is suitable for, but not limited to, models using a process description approach.\nThe latest stable specification is Level 3 Version 2 Core.\nSBML development is coordinated by an elected editorial board and central developer team.\nOver 250 software systems known to support SBML can be found in the SBML software documentation. APIs are available to help implementing support: libSBML in C++ and JSBML in Java.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"1b40cb17ded60a8ba357dd6a041bbf8a","permalink":"/author/sbml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbml/","section":"authors","summary":"The Systems Biology Markup Language (SBML) is a computer-readable XML format for representing models of biological processes. SBML is suitable for, but not limited to, models using a process description approach.","tags":null,"title":"SBML","type":"authors"},{"authors":["SBO"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"1b887e1ad8322019d9528e2b1a367143","permalink":"/author/sbo/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbo/","section":"authors","summary":"","tags":null,"title":"SBO","type":"authors"},{"authors":["SBOL"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"4953ae5addbde52a0d1556d99b970ae7","permalink":"/author/sbol/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbol/","section":"authors","summary":"","tags":null,"title":"SBOL","type":"authors"},{"authors":["SBOL"],"categories":null,"content":"The Synthetic Biology Open Language Data (SBOL Data) is a language for the description and the exchange of synthetic biological parts, devices and systems.\nThe latest stable specification of SBOL Data is 3.1.0.\nSBOL Data is developed by the SBOL Developers Group. The development is coordinated by an editorial board and the SBOL Chair.\nSBOL data is supported by many software tools. APIs are available to help implement the support of this data standard.\nMore information\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"0655cb362e203e114be044cb4212d191","permalink":"/author/sbol/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbol/","section":"authors","summary":"The Synthetic Biology Open Language Data (SBOL Data) is a language for the description and the exchange of synthetic biological parts, devices and systems.\nThe latest stable specification of SBOL Data is 3.","tags":null,"title":"SBOL","type":"authors"},{"authors":["SBOL Visual"],"categories":null,"content":"The Synthetic Open Language Visual (SBOL Visual) is an open-source graphical notation that uses schematic “glyphs” to specify genetic parts, devices, modules, and systems.\nThe latest stable specification of SBOL Visual is 3.0.0.\nSBOL is developed by the SBOL Developers Group and SBOL Visual Group. The development is coordinated by an editorial board and the SBOL Chair.\nSBOL Visual is supported by many software tools.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"ce1d619208f042ec7ca1f568ced5824b","permalink":"/author/sbol-visual/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sbol-visual/","section":"authors","summary":"The Synthetic Open Language Visual (SBOL Visual) is an open-source graphical notation that uses schematic “glyphs” to specify genetic parts, devices, modules, and systems.\nThe latest stable specification of SBOL Visual is 3.","tags":null,"title":"SBOL Visual","type":"authors"},{"authors":["SED-ML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bc3da178a82252db073443dec523497b","permalink":"/author/sed-ml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sed-ml/","section":"authors","summary":"","tags":null,"title":"SED-ML","type":"authors"},{"authors":["SED-ML"],"categories":null,"content":"The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format for encoding simulation experiments. SED-ML allows to define the models to use, the experimental tasks to run and which results to produce.is a computer-readable format for representing the models of biological processes. SED-ML can be used with models encoded in several languages, as far as they are in XML.\nThe latest stable specification is Level 1 Version 5.\nSED-ML development is coordinated by an elected editorial board.\nAPIs are available to help implementing support: libSedML in C#, libSEDML in C++ with swig bindings for python, java, perl, R and ruby, and jlibsedml in Java.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"29da9d6440f54627c606f2ceb7f6cec3","permalink":"/author/sed-ml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sed-ml/","section":"authors","summary":"The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format for encoding simulation experiments. SED-ML allows to define the models to use, the experimental tasks to run and which results to produce.","tags":null,"title":"SED-ML","type":"authors"},{"authors":["SpineML"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2f77ace67afab444cd4a8d2f2010eff8","permalink":"/author/spineml/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/spineml/","section":"authors","summary":"","tags":null,"title":"SpineML","type":"authors"},{"authors":["TEDDY"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bc0f1f1f4c317dfac42f22e2a51d41c0","permalink":"/author/teddy/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/teddy/","section":"authors","summary":"","tags":null,"title":"TEDDY","type":"authors"},{"authors":["Thomas Gorochowski"],"categories":null,"content":"Thomas Gorochowski (Ph.D. in Engineering Mathematics) is a Royal Society University Research Fellow and Lecturer at the University of Bristol, UK where he heads up the Biocompute Lab. His research is focused on better understanding how biological systems process information and exploiting synthetic biology techniques to rationally reprogram living cells with our own desired functions. Since 2016 he has been involved with the SBOL Data and Visual standards and is currently a member of the SBOL Scientific Steering Committee.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"24db5b2a879bf2c3c85a2bd30c29c6eb","permalink":"/author/thomas-gorochowski/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/thomas-gorochowski/","section":"authors","summary":"Thomas Gorochowski (Ph.D. in Engineering Mathematics) is a Royal Society University Research Fellow and Lecturer at the University of Bristol, UK where he heads up the Biocompute Lab. His research is focused on better understanding how biological systems process information and exploiting synthetic biology techniques to rationally reprogram living cells with our own desired functions.","tags":null,"title":"Thomas Gorochowski","type":"authors"},{"authors":null,"categories":null,"content":"   Name Affiliation Attendance     Mihail Anton Chalmers University of Technology Friday 7th OctoberCOMBINE Archive and OMEX, FROG, ModeleXchange, Personalized Medicine, SBGN   Lara BRUEZIERE Novadiscovery Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBGN, SBML, SED-ML   Irina Balaur University of Luxembourg Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, SBGN   Jacob Barhak Jacob Barhak Analytics Friday 7th October, Saturday 8th OctoberModeleXchange, SBML   Bryan Bartley Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Florian Bartsch Institut für theoretische Biologie, Humboldt-Universität zu Berlin Thursday 6th October, Friday 7th OctoberPersonalized Medicine, SBML   Jacob Beal Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Frank Bergmann Heidelberg University, BioQUANT / COS Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, PEtab, SBGN, SBML, SED-ML   Michael Blinov UConn Health Friday 7th October, Saturday 8th OctoberBioPAX, COMBINE Archive and OMEX, ModeleXchange, PEtab, SBGN, SBML, SED-ML   Lutz Brusch Technische Universität Dresden Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, PEtab, MultiCellML, MorpheusML, SBML-Spatial   Daniel Bryce SIFT, LLC. Thursday 6th October, Friday 7th October, Saturday 8th October-   Lukas Buecherl University of Colorado Boulder Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, Personalized Medicine, SBML, SBOL, SBOL Visual, SED-ML   Zsófia Bujtár Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Berlin) Friday 7th October, Saturday 8th OctoberSBGN, SBML, DDE-BIFTOOL   Famke Bäuerle University of Tuebingen Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, Personalized Medicine, SBGN, SBML, SED-ML   Jeremy Cahill Metamer Labs Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, NeuroML, Personalized Medicine, PEtab, SBGN, SBML, SBOL, SBOL Visual, SED-ML   Marie Coutelier Paris Brain Institute -CellML, COMBINE Archive and OMEX, NeuroML, Personalized Medicine   Tobias Czauderna University of Applied Sciences Mittweida Friday 7th October, Saturday 8th OctoberSBGN   James Diggans Twist Bioscience Thursday 6th OctoberSBOL, SBOL Visual   Andreas Dräger Eberhard Karls Universität Tübingen Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, SBGN, SBML, SED-ML   Dorotea Dudas HITS gGmbH Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Ibrahim Dulijan stevens.edu Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML, SBOL, SBOL Visual   Longxuan Fan University of Washington Thursday 6th OctoberSBML   Fabian Fröhlich Harvard Medical School Friday 7th October, Saturday 8th OctoberBioPAX, PEtab, SBML, SED-ML   Alan Garny University of Auckland Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, SED-ML   Robert T. Giessmann Institute for globally distributed open research and education (IGDORE) -BioPAX, COMBINE Archive and OMEX, SBML, SBOL, SBOL Visual, SED-ML, thermodynamic data, openTECR   Mose Giordano UCL Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Thomas Gorochowski University of Bristol Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Alexander Gower Chalmers University of Technology Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, PEtab, SBGN, SBML, SED-ML   Niklas Gröne Universität Konstanz Thursday 6th October, Friday 7th October, Saturday 8th October-   Roy Gusinow University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML, PEtab, SBML   Lea Gütebier Department of Medical Informatics, Institute for Community Medicine, University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, Personalized Medicine, SBML, SED-ML   Jan Hasenauer University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberModeleXchange, Personalized Medicine, PEtab, SBGN, SBML, SED-ML   Joseph Hellerstein eScience Institute, University of Washington Thursday 6th OctoberSBML, SED-ML   Joseph Hellerstein University of Washington Thursday 6th OctoberPEtab, SBML, SED-ML   Ron Henkel University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, ModeleXchange, SBGN, SBML, SBOL, SED-ML   Henning Hermjakob EMBL-EBI Friday 7th October, Saturday 8th OctoberBioPAX, COMBINE Archive and OMEX, FROG, ModeleXchange, SBML   Sebastian Höpfl Institute for Systems Theory and Automatic Control (IST) Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, PEtab, SBML   Johann Fredrik Jadebeck IBG-1 Forschungszentrum Jülich Thursday 6th October, Saturday 8th OctoberFROG, SBML   João Júnior Centro de Tecnologia Canavieira Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, ModeleXchange, Personalized Medicine, SED-ML   Miroslav Kratochvíl Luxembourg Centre for Systems Biomedicine Saturday 8th OctoberFROG, SBML   Olga Krebs Heidelberg Institute for Theoretical Studies Thursday 6th October, Friday 7th October, Saturday 8th OctoberPersonalized Medicine, PEtab, SBML, SBOL, SBOL Visual, SED-ML   Adrian Köller Institut für theoretische Biologie, Humboldt-Universität zu Berlin Thursday 6th October, Friday 7th OctoberSBML   Matthias König Humboldt-University Berlin Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, Personalized Medicine, PEtab, SBML, SED-ML   Paul Lang University of Oxford; Julia Computing Saturday 8th OctoberPersonalized Medicine, PEtab, SBML   Eva Liu University of Washington Bioengineering Sys-Bio Lab Thursday 6th October-   Sebastian Lobentanzer University Hospital Heidelberg Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, Personalized Medicine, PEtab, SBGN, SBML   Augustin Luna Harvard Medical School Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, SBGN   Karin Lundengård Auckland Bioengineering Institute Thursday 6th October, Friday 7th October-   Steve Ma NVIDIA Thursday 6th OctoberSBML   Simon Merkt University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML, PEtab, SBGN, SBML   Lukrécia Mertová Heidelberg Institute for Theoretical Studies HITS gGmbH Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, ModeleXchange, Personalized Medicine, SBML, SBOL   Goksel Misirli Keele University Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Ion Moraru UConn Health Thursday 6th October, Friday 7th OctoberCOMBINE Archive and OMEX, SBML, SED-ML   Sébastien Moretti SIB Swiss Institute of Bioinformatics Thursday 6th October, Friday 7th OctoberSBML   Chris Myers University of Colorado Boulder Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual, SBML, SED-ML   Tung Nguyen EMBL-EBI Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, FROG, ModeleXchange, Personalized Medicine, PEtab, SBGN, SBML, SED-ML   David Nickerson Auckland Bioengineering Institute, University of Auckland Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, PEtab, SED-ML   Dilan Pathirana University of Bonn Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML   Clemens Peiter IRU MLS, LIMES, University of Bonn Thursday 6th October, Friday 7th OctoberPEtab, SBGN, SBML   Sathish Periyasamy Queensland Brain Institute Friday 7th October, Saturday 8th OctoberCellML, NeuroML, Personalized Medicine, SBGN, SBML   Fronth Nyus Pi Quantum4Life Sensonomiqs Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, NeuroML, SBML, SBOL   Veronica Porubsky University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberNeuroML   Nicole Radde University of Stuttgart Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, PEtab, SBML   Karthik Raman Indian Institute of Technology Madras Thursday 6th October, Friday 7th October, Saturday 8th OctoberFROG   Gianmarco Rasi - Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Susana Roman Garcia University of Edinburgh Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, CellML, COMBINE Archive and OMEX, ModeleXchange, NeuroML, Personalized Medicine, PEtab, SBGN, SBML, SBOL, SBOL Visual, SED-ML   Adrien Rougny Independent researcher (former AIST) Friday 7th October, Saturday 8th OctoberSBGN   Herbert Sauro University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, SBML, SED-ML   Falk Schreiber University of Konstanz Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBGN, SBML, SBOL Visual   James Scott-Brown University of Edinburgh Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Vinoo Selvarajah iGEM Foundation Thursday 6th October, Friday 7th OctoberSBOL, SBOL Visual   Woosub Shin Auckland Bioengineering Institute, University of Washington -SBML   Lucian Smith University of Washington Thursday 6th October, Friday 7th October, Saturday 8th OctoberCellML, COMBINE Archive and OMEX, FROG, PEtab, SBML, SED-ML   Jörn Starruß TU Dresden Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML, MultiCellML   Melanie Stefan Medical School Berlin Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, SBGN, SBML   Abel Szkalisity University of Helsinki Thursday 6th October, Friday 7th October, Saturday 8th OctoberBioPAX, SBML   Baishakhi Tikader Indian Institute of Bombay, India Friday 7th OctoberSBML   Krishna Kumar Tiwari EMBL-EBI Thursday 6th October, Friday 7th October, Saturday 8th OctoberFROG, ModeleXchange, Personalized Medicine, SBGN   Matej Troják Masaryk university Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBML   Adelinde Uhrmacher University of Rostock Saturday 8th OctoberCellML, COMBINE Archive and OMEX, SBGN, SBML, SED-ML   Prashant Vaidyanathan Oxford Biomedica Thursday 6th October, Friday 7th OctoberSBOL   Paola Vera-Licona UConn Health Friday 7th OctoberBioPAX, Personalized Medicine, SBML   Gonzalo Vidal ICOS, Newcastle University Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Dagmar Waltemath University Medicine Greifswald Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, Personalized Medicine, SBML, SED-ML, FAIR model indicators   Daniel Weindl Helmholtz Munich Thursday 6th October, Friday 7th October, Saturday 8th OctoberPEtab, SBML, SED-ML   St. Elmo Wilken Heinrich Heine University Saturday 8th October-   Pia Wilsdorf University of Rostock Saturday 8th OctoberCOMBINE Archive and OMEX, PEtab, SED-ML   Fengkai Zhang NIAID/NIH Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, ModeleXchange, SBGN, SBML, SED-ML   kristina gruden NIB Saturday 8th OctoberCellML, SBGN, SBML, SBOL    ","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"7b5389fe8a894e0390d3700a34967c71","permalink":"/author/combine-2022/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2022/","section":"authors","summary":"Name Affiliation Attendance     Mihail Anton Chalmers University of Technology Friday 7th OctoberCOMBINE Archive and OMEX, FROG, ModeleXchange, Personalized Medicine, SBGN   Lara BRUEZIERE Novadiscovery Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBGN, SBML, SED-ML   Irina Balaur University of Luxembourg Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, Personalized Medicine, SBGN   Jacob Barhak Jacob Barhak Analytics Friday 7th October, Saturday 8th OctoberModeleXchange, SBML   Bryan Bartley Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Florian Bartsch Institut für theoretische Biologie, Humboldt-Universität zu Berlin Thursday 6th October, Friday 7th OctoberPersonalized Medicine, SBML   Jacob Beal Raytheon BBN Thursday 6th October, Friday 7th October, Saturday 8th OctoberSBOL, SBOL Visual   Frank Bergmann Heidelberg University, BioQUANT / COS Thursday 6th October, Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, FROG, PEtab, SBGN, SBML, SED-ML   Michael Blinov UConn Health Friday 7th October, Saturday 8th OctoberBioPAX, COMBINE Archive and OMEX, ModeleXchange, PEtab, SBGN, SBML, SED-ML   Lutz Brusch Technische Universität Dresden Friday 7th October, Saturday 8th OctoberCOMBINE Archive and OMEX, PEtab, MultiCellML, MorpheusML, SBML-Spatial   Daniel Bryce SIFT, LLC.","tags":null,"title":"","type":"authors"},{"authors":null,"categories":null,"content":"   Name Affiliation Attendance Projects     Amir Mahari University of Arkansas Oct 5 Oct 6 Oct 7 Oct 8 SBML;SBGN;Multicellular modeling   Augustin Luna Harvard Medical School remotely SBGN;BioPAX   Bharat Mishra PhD  SBML;SED-ML, OMEX, COMBINE;CellML;Ontologies (SBO, KiSAO);Multicellular modeling   Chris Myers University of Colorado Boulder Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual   Dagmar Waltemath University Medicine Greifswald remotely SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO)   Daniel Ajuzie undergraduate Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual;CellML;Ontologies (SBO, KiSAO);Multicellular modeling   Daniel Ajuzie undergraduate Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;CellML;NeuroML   Diego Jahn TUD Dresden University of Technology, Center for Information Services and High Performance Computing (ZIH) Oct 5 Oct 6 Multicellular modeling   Egils Stalidzans PhD  SBML;SBOL, SBOL visual   Elebeoba May University of Wisconsin-Madison  SBML;Multicellular modeling;Visualization   Fengkai Zhang NIH  SBML;SED-ML, OMEX, COMBINE;SBGN   Frank T. Bergmann BioQUANT, Heidelberg University Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN   Gaoxiang Zhou University of Pittsburgh Oct 5 Oct 6 Oct 7 Oct 8 SBML;BioPAX;SBOL, SBOL visual;CellML;Multicellular modeling   Gerhard Mayer HITS (Heidelberg Institute for Theoretical Studies) gGmbH, Heidelberg remotely SED-ML, OMEX, COMBINE;Multicellular modeling   James A. Glazier Indiana University Oct 5 Oct 6 Oct 7 Oct 8 Multicellular modeling   John Gennari University of Washington Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;BioPAX;CellML;Ontologies (SBO, KiSAO)   Juliano Ferrari Gianlupi Postdoctoral Scholar, UTHSC  SBML;CellML;Multicellular modeling   Jörn Starruß Technische Universität Dresden, Germany remotely SBML;SED-ML, OMEX, COMBINE;CellML;Multicellular modeling   Jürgen Pahle Heidelberg University Oct 5 Oct 6 Oct 7 Oct 8 -   Lea Seep University Bonn, IRU-MLS  SBML;Ontologies (SBO, KiSAO)   Luis Fonseca University of Florida remotely SBML;SBGN;CellML;NeuroML;Multicellular modeling;ABM   Lukas Buecherl University of Colorado Boulder  SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual   Lutz Brusch Technische Universität Dresden, Germany  Multicellular modeling   Maren Philipps University of Bonn Oct 5 Oct 6 Oct 7 Oct 8 -   Mauro Silberberg Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, y CONICET - Universidad de Buenos Aires, Instituto de Física de Buenos Aires (IFIBA). Buenos Aires, Argentina remotely SBML;SED-ML, OMEX, COMBINE;CellML;NeuroML   Michael Blinov Center for Cell Analysis and Modeling, UConn Health, Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN;BioPAX;Ontologies (SBO, KiSAO);Multicellular modeling   Mustafa Ozen Altos Labs  SED-ML, OMEX, COMBINE;CellML;NeuroML;Multicellular modeling   Nilesh Kumar PhD  SBML;SED-ML, OMEX, COMBINE;CellML   Olga Krebs Heidelberg Institute for Theoretical Studies HITS  SED-ML, OMEX, COMBINE;SBOL, SBOL visual;Ontologies (SBO, KiSAO);BioProtocols   Rahuman Sheriff European Bioinformatics Institute (EMBL-EBI) Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBGN;Ontologies (SBO, KiSAO);Multicellular modeling;FROG   Sebastien Moretti SIB Swiss Institute of Bioinformatics remotely SBML;Ontologies (SBO, KiSAO)   Sikao Guo PostDoc Oct 5 Oct 6 Oct 7 Oct 8 SBML;BioPAX;CellML;NeuroML;Multicellular modeling   T.J. Sego University of Florida Oct 5 Oct 6 Oct 7 Oct 8 SBML;Multicellular modeling    ","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"293972840fc694a4a7544b079eae21a3","permalink":"/author/combine-2023/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2023/","section":"authors","summary":"Name Affiliation Attendance Projects     Amir Mahari University of Arkansas Oct 5 Oct 6 Oct 7 Oct 8 SBML;SBGN;Multicellular modeling   Augustin Luna Harvard Medical School remotely SBGN;BioPAX   Bharat Mishra PhD  SBML;SED-ML, OMEX, COMBINE;CellML;Ontologies (SBO, KiSAO);Multicellular modeling   Chris Myers University of Colorado Boulder Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual   Dagmar Waltemath University Medicine Greifswald remotely SED-ML, OMEX, COMBINE;Ontologies (SBO, KiSAO)   Daniel Ajuzie undergraduate Oct 5 Oct 6 Oct 7 Oct 8 SBML;SED-ML, OMEX, COMBINE;SBOL, SBOL visual;CellML;Ontologies (SBO, KiSAO);Multicellular modeling   Daniel Ajuzie undergraduate Oct 5 Oct 6 Oct 7 SBML;SED-ML, OMEX, COMBINE;CellML;NeuroML   Diego Jahn TUD Dresden University of Technology, Center for Information Services and High Performance Computing (ZIH) Oct 5 Oct 6 Multicellular modeling   Egils Stalidzans PhD  SBML;SBOL, SBOL visual   Elebeoba May University of Wisconsin-Madison  SBML;Multicellular modeling;Visualization   Fengkai Zhang NIH  SBML;SED-ML, OMEX, COMBINE;SBGN   Frank T.","tags":null,"title":"","type":"authors"},{"authors":null,"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"5188e029e3edaccf99026e4ed5af1d80","permalink":"/author/combine-2024/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/combine-2024/","section":"authors","summary":"","tags":null,"title":"","type":"authors"},{"authors":null,"categories":null,"content":"The following are the registered attendees for HARMONY 2026, as of 2026-01-29 01:28 UTC.\n   Name Affiliation Attendance Interests     Hugh Sorby Auckland Bioengineering Institute In person CellML, SED-ML   Falk Schreiber University of Konstanz In person SBGN, SBML, SBOL and SBOL Visual   Alan Garny University of Auckland In person CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SED-ML   Weiwei Ai Auckland Bioengineering Institute, University Of Auckland In person CellML, SED-ML, PE-TAB   Xiaoming Hu Bioquant, University Heidelberg In person SBML, Data Management, Ro-Crate   Lucian Smith University of Washington In person COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBML, SED-ML, FROG   Chris Myers University of Colorado Boulder In person COMBINE Archive, SBML, SBOL and SBOL Visual, SED-ML   Frank T. Bergmann BioQUANT, Heidelberg University In person COMBINE Archive, SBGN, SBML, SED-ML, PE-TAB, FROG   David Nickerson Auckland Bioengineering Institute, University of Auckland In person CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SED-ML, PE-TAB, repositories; model publishing   Eric Young WPI In person SBOL and SBOL Visual   Triana Karnadipa ABI Remotely COMBINE Archive, NeuroML, OMEX Metadata   Pedro T. Monteiro IST - University of Lisbon Remotely Multicellular Modelling, SBML, SED-ML, FROG   MORETTI Sébastien SIB Swiss Institute of Bioinformatics Remotely BioPAX, SBGN, SBML   Ayesha Abubakr St. John\u0026rsquo;s Kilmarnock School Remotely BioPAX, CellML, Multicellular Modelling, NeuroML, SBML, SBOL and SBOL Visual, SED-ML   Gonzalo Vidal University of Colorado Boulder Remotely SBOL and SBOL Visual   Hoda Rahimi The University of Auckland Remotely BioPAX, CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB   Litian Su Auckland Bioengineering Institute Remotely CellML, SBML   Maria Chiara Langella University of Naples Federico II Remotely BioPAX, CellML, COMBINE Archive, Multicellular Modelling, SBML, SBOL and SBOL Visual, PE-TAB   Leo Willyanto Santoso Auckland Bioengineering Institute, The University of Auckland Remotely CellML   Koray Atalag Auckland Bioengineering Institute Remotely health data interoperability (FHIR, openEHR, SNOMED, LOINC, ICD etc.)   Lutz Brusch TU Dresden, Germany Remotely Multicellular Modelling, SBML, PE-TAB, OpenVT, MultiCellML, MorpheusML   Jarrah Dowrick Auckland Bioengineering Institute In person CellML, COMBINE Archive, OMEX Metadata, SBGN, SED-ML, FieldML   Goksel Misirli Keele University Remotely Multicellular Modelling, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual    University at Buffalo Remotely    Marc Molla Garcia UPF In person BioPAX, CellML, COMBINE Archive, Multicellular Modelling, NeuroML, OMEX Metadata, SBGN, SBML, SBOL and SBOL Visual, SED-ML, PE-TAB, FROG   Matthias König Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Biology, Institute of Theoretical Biology, Systems Medicine of the Liver; University of Stuttgart, Institute of Structural Mechanics and Dynamics in Aerospace Engineering Remotely CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG   Augustin Luna National Library of Medicine Remotely BioPAX, SBGN   Hasan Balci National Library of Medicine, NIH Remotely SBGN, SBML   Fengkai Zhang NIH, US Remotely COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBOL and SBOL Visual, SED-ML, PE-TAB   Te Chen Technical University of Denmark Remotely SBML, SED-ML   Viola Rintoul UW Madison Remotely CellML, COMBINE Archive, Multicellular Modelling, SBOL and SBOL Visual, SED-ML   Rahuman Sheriff EMBL-EBI Remotely CellML, COMBINE Archive, Multicellular Modelling, OMEX Metadata, SBGN, SBML, SED-ML, PE-TAB, FROG    ","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"83af3397e10144788ed36d174d2dfef4","permalink":"/author/harmony-2026/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harmony-2026/","section":"authors","summary":"The following are the registered attendees for HARMONY 2026, as of 2026-01-29 01:28 UTC.\n   Name Affiliation Attendance Interests     Hugh Sorby Auckland Bioengineering Institute In person 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