PaccMann/TITAN
Code for "T Cell Receptor Specificity Prediction with Bimodal Attention Networks" (https://doi.org/10.1093/bioinformatics/btab294, ISMB 2021)
This project helps immunologists and drug discovery scientists predict which T-cell receptors (TCRs) will bind to specific disease-related epitopes. You input CSV files containing TCR sequences, epitope sequences (either amino acid or chemical structure), and known binding relationships. The output is a trained model that can predict new TCR-epitope interactions, which is valuable for understanding immune responses and developing new therapies.
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Use this if you need to predict T-cell receptor specificity for various epitopes, such as for vaccine development or cancer immunotherapy.
Not ideal if you are working with protein-ligand interactions outside of the TCR-epitope context.
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Jupyter Notebook
License
MIT
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Last pushed
Jul 12, 2025
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