Systems biology informed deep learning for inferring parameters and hidden dynamics

The code for the paper A. Yazdani, L. Lu, M. Raissi, & G. E. Karniadakis. Systems biology informed deep learning for inferring parameters and hidden dynamics. PLoS Computational Biology, 16(11), e1007575, 2020.

Code

The code depends on the deep learning package DeepXDE v0.10.0. If you want to use the latest DeepXDE, you need to replace dde.bc.PointSet with dde.PointSetBC. You can also find the updated code at https://github.com/lu-group/sbinn.

• glycolysis.py: Yeast glycolysis model
• apoptosis.py: Cell apoptosis model
• glucose_insulin.py: Ultradian endocrine model
• FIM.ipynb: Fisher information matrix. This code is written in Julia.

Cite this work

If you use this code for academic research, you are encouraged to cite the following paper:

@article{yazdani2020systems,
  title   = {Systems biology informed deep learning for inferring parameters and hidden dynamics},
  author  = {Yazdani, Alireza and Lu, Lu and Raissi, Maziar and Karniadakis, George Em},
  journal = {PLoS computational biology},
  volume  = {16},
  number  = {11},
  pages   = {e1007575},
  year    = {2020}
}

Questions

To get help on how to use the code, simply open an issue in the GitHub "Issues" section.