TACTIC

Transfer learning And Crowdsourcing to predict Therapeutic Interactions Cross-species.

Summary

This GitHub repository contains all code and data files used to develop the TACTIC approach (citation below).

Chung, C. H., Chang, D. C., Rhoads, N. M., Shay, M. R., Srinivasan, K., Okezue, M. A., Brunaugh, A. D., and Chandrasekaran, S. (2024). Transfer learning predicts species-specific drug interactions in emerging pathogens. bioRxiv preprint

Repository structure:

TACTIC
└───data                        [directory containing all relevant data files]
|   LICENSE
|   README.md
|   TACTIC_analysis.ipynb       [Jupyter Notebook containing all analyses described in TACTIC manuscript]
|   TACTIC_logo.png             [PNG file for TACTIC logo]
|   TACTIC_tutorial.ipynb       [Jupyter notebook that guides a new user on how to use the already built TACTIC model]
|   TACTIC_visualization.ipynb  [Jupyter Notebook that visualizes all TACTIC manuscript outputs]

License

Released via GPL GNU License
© 2024 The Regents of the University of Michigan
Chandrasekaran Research Group - https://systemsbiologylab.org/
Contact: csriram@umich.edu