In silico screening of immunogenic epitopes among the vast amount of MHC-loaded peptides is a critical step toward effective precision immunotherapy. Although various sequence-based prediction models have been proposed, none of them has ever achieved meaningful accuracy and robustness. Here, we developped a framework that enables accurate classification of immunogenic epitopes and non-immunogenic MHC binders through simulating contacts between MHC-presented peptides and public human TCR repertoire.
|Maintainer||Masato Ogishi <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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