We build biological software for a world that needs smarter, safer, and more sustainable technologies.

The DRAGGON Lab is an interdisciplinary research lab opening at the University of Bristol. We work at the frontier of synthetic biology, computer science, biochemistry, artificial intelligence, and biological engineering to make genetic and genomic networks programmable.

Our core idea is simple and powerful:

DNA is software. Biology is hardware. The future needs better tools to program both.

We are developing the scientific foundations, open-source software, automated workflows, and intelligent biological systems needed to engineer living matter with the reliability, scalability, and creativity that transformed modern computing.

Our long-term goal is to help as many people as possible by creating technologies for human health, sustainable agriculture, resilient ecosystems, biomanufacturing, environmental monitoring, and planetary-scale challenges.

Modern society faces enormous challenges: disease, food insecurity, climate change, biodiversity loss, unsustainable manufacturing, and the need for more adaptive technologies.

Biology already solves problems that are difficult for traditional engineering. Cells can sense, compute, grow, heal, adapt, manufacture, communicate, and self-organize. But today, designing biology is still too slow, too artisanal, and too hard to scale.

The DRAGGON Lab exists to change that.

We are building the infrastructure for biological software engineering: tools that allow researchers and companies to design biological systems on computers, simulate them across scales, build them with automation, test them with high-quality data, and learn from every experiment.

We imagine a future where engineering biology is as programmable, shareable, reusable, and transformative as software engineering.

The DRAGGON Lab develops computer-aided biodesign platforms that connect computational ideas to engineered biological function.

We aim to make it possible to:

• Write computational specifications and compile them into genetic designs.
• Design genetic and genomic networks with predictable behavior.
• Build automated design-build-test-learn workflows for synthetic biology.
• Train AI models on high-quality biological data.
• Simulate cells, communities, host-microbiomes, and ecosystems before building them.
• Create intelligent organisms and communities that sense, compute, report, produce, and respond.
• Translate discoveries into useful, responsible technologies for society.

In one sentence:

We are building the tools to program living systems for human and planetary health.

We develop open-source tools and standards-enabled platforms for representing, designing, tracking, building, testing, and learning from biological systems.

Biology needs the equivalent of compilers, version control, simulation engines, package managers, design languages, metadata standards, and debugging tools. DRAGGON Lab builds this infrastructure so the community can engineer biology more reproducibly, collaboratively, and safely.

Our software ecosystem includes tools for:

• Synthetic biology design representation.
• Genetic network design automation.
• Physical and digital inventory tracking.
• Promoter and operator prediction.
• Agent-based simulations.
• Standardized data and metadata capture.
• Experimental database integration.
• Automated DBTL workflows.

The design-build-test-learn cycle is the engine of synthetic biology.

We connect software, robotics, experimental databases, and machine learning so that every experiment produces reusable knowledge. Our workflows are designed to scale from small academic laboratories to biofoundries and industrial facilities.

The goal is not automation for its own sake. The goal is better science: experiments that are traceable, reproducible, interpretable, and useful for training the next generation of biological AI models.

Pure AI can be powerful, but biology needs models that understand mechanism, context, and uncertainty.

We develop biochemistry-informed machine learning, graph-based models, multimodal models, and hybrid mechanistic-AI approaches to predict gene expression, regulation, and biological function from sequence, structure, context, and metadata.

We are especially interested in AI systems that do not simply produce answers, but help scientists reason: models that explain assumptions, connect to design tools, propose experiments, and improve through the DBTL cycle.

Before deploying a biological system, we should understand how it behaves across scales.

We develop and use simulation engines to create digital twins of biological systems: single cells, microbial populations, bacterial colonies, host-microbiome interactions, plant-microbiome systems, and spatial communities.

These simulations help us explore questions that are difficult or impossible to test directly at first:

• How will an engineered cell behave in a changing environment?
• How do local interactions create global patterns?
• How can microbial communities be steered toward beneficial states?
• How can engineered organisms communicate with machines, sensors, or hosts?
• How do we design biological systems that are robust, safe, and useful?

At the heart of DRAGGON Lab is the engineering of genetic and genomic networks.

We design biological systems in which DNA, RNA, proteins, chemicals, cells, and communities become computationally meaningful components. We work toward biological systems that can sense inputs, process information, make decisions, produce outputs, and report their state.

This includes future directions such as biological artificial intelligence, reservoir computing, dynamical genetic networks, biosensors, intelligent microbial communities, and engineered host-associated systems.

DRAGGON Lab is a platform lab. Our tools are designed to enable many applications.

We are particularly excited about:

• Bacteria-as-medicine.
• Smart biosensors.
• Engineered microbiomes.
• Skin and gut host-microbiome systems.
• Biological systems that detect, report, or respond to disease states.

• Plant-microbiome engineering.
• Resilient crops.
• Nutrient-enhanced production systems.
• Biological sensing for crop state and soil health.
• Distributed, adaptive, locally programmable agriculture.

• Bio-based production of materials and chemicals.
• Environmental monitoring.
• Microbial and plant systems for constrained environments.
• Biological platforms for sustainable manufacturing.

• AI-assisted strain and pathway design.
• Automated biological design workflows.
• Standards-enabled data generation.
• Biofoundry-ready software infrastructure.
• Predictive tools for faster translation from idea to product.

DRAGGON Lab sits at the convergence of several major technology shifts:

• AI is transforming biological discovery.
• Synthetic biology is becoming an engineering discipline.
• Lab automation is increasing the scale of biological data.
• Open standards are making biological designs more reusable.
• Biomanufacturing and living technologies are becoming strategic capabilities.

We are building the connective tissue between these shifts.

Our work creates value by turning fragmented biological experiments into programmable, data-rich, automated engineering workflows. That creates opportunities for new medicines, agricultural systems, industrial processes, AI models, software platforms, and spinout-ready technologies.

For funding agencies, DRAGGON Lab offers a rigorous interdisciplinary programme that combines fundamental science, open infrastructure, responsible innovation, and high-impact applications.

For venture investors and translational partners, DRAGGON Lab offers a platform vision: reusable biological design infrastructure that can support multiple product verticals across health, agriculture, environment, and biomanufacturing.

We believe the future of engineering biology must be collaborative.

DRAGGON Lab develops open-source software and contributes to community standards so that biological engineering can become more transparent, reproducible, and interoperable.

We care deeply about:

• FAIR data.
• Standardized metadata.
• Reusable genetic designs.
• Reproducible computational workflows.
• Community-driven software.
• Responsible research and innovation.
• Clear documentation.
• Training the next generation of interdisciplinary scientists and engineers.

Open infrastructure accelerates science. It also creates trust.

DRAGGON Lab is built for people who are excited by difficult problems and generous collaboration.

We welcome students, researchers, engineers, designers, and collaborators from biology, computer science, mathematics, engineering, chemistry, physics, medicine, agriculture, design, and entrepreneurship.

Our training philosophy is project-oriented and student-centered. Members of the lab learn by building, testing, explaining, documenting, and improving real tools and systems.

We aim to create an environment where people:

• Think independently.
• Learn across disciplines.
• Build useful technologies.
• Communicate clearly.
• Share credit.
• Respect different backgrounds and experiences.
• Connect theory with practice.
• Use science and engineering in service of society.

The lab’s ambition is high, but the culture is human: rigorous, kind, creative, collaborative, and brave.

Our GitHub organization hosts tools and repositories connected to biological design automation, synthetic biology standards, simulation, prediction, and data management.

Projects include work around:

• LOICA — genetic network design automation.
• SimBOL — connecting SBOL designs to agent-based simulations.
• WebCM — web-based bacterial simulations.
• Ouroboros — promoter and promoter-activity prediction.
• KaiTen — operator-site and protein-DNA interaction prediction.
• LADON — genetic network inference.
• SynBioInventory / SBOLInventory — standards-enabled synthetic biology inventory.
• Flapjack — experimental data infrastructure for synthetic biology workflows.
• AoGuang — standards-enabled DNA annotation.

Some tools are mature, some are prototypes, and some are emerging research directions. Together, they form the beginning of a larger platform for biological software engineering.

We are looking for collaborators, students, funders, and partners who want to build the future of engineering biology.

We are especially interested in collaborations around:

• AI for synthetic biology.
• Computer-aided biodesign.
• Lab automation and biofoundries.
• Biological standards and FAIR data.
• Genetic network engineering.
• Agent-based biological simulation.
• Host-microbiome digital twins.
• Plant-microbiome engineering.
• Biosensors and smart biological reporters.
• Translational biotechnology for health, agriculture, sustainability, and biomanufacturing.

If you are a scientist, engineer, student, founder, investor, policymaker, or member of the public excited by responsible biological innovation, we would love to hear from you.

The twentieth century gave us electronics. The twenty-first century is giving us programmable biology.

DRAGGON Lab is building the tools, models, workflows, and communities needed to make that future rigorous, responsible, and useful.

We want a world where biological systems can be designed with clarity, tested with confidence, shared with integrity, and deployed for the benefit of people and the planet.

Welcome to DRAGGON Lab. Let’s program life responsibly.