SBINN: Systems-biology informed neural network

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Deep Learningsbinn
Overview

SBINN: Systems-biology informed neural network

The source code for the paper M. Daneker, Z. Zhang, G. E. Karniadakis, & L. Lu. Systems biology: Identifiability analysis and parameter identification via systems-biology informed neural networks. arXiv preprint arXiv:2202.01723, 2022.

Code

Cite this work

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

@article{daneker2022systems,
  title={Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks}, 
  author={Mitchell Daneker and Zhen Zhang and George Em Karniadakis and Lu Lu},
  year={2022},
  eprint={2202.01723},
  archivePrefix={arXiv}
}

Questions

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

Owner
Lu Group
Lu Group, Department of Chemical and Biomolecular Engineering, University of Pennsylvania
Lu Group
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