Article

Predicting TCR-pMHC Binding by Reinforcement Learning

2026-01-05

Abstract excerpt

The binding between T cell receptors (TCRs) and peptide-major histocompat-ibility complexes (pMHCs) is fundamental to the immune system’s ability to recognize and eliminate pathogens. Accurate prediction of TCR-pMHC inter-actions holds significant promise for advancing cancer immunotherapy, vaccine design, and autoimmune disease research. However, existing approaches often treat the sequences, structures, and func...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: ed80707f-ad43-5ed3-80a0-f8d259d34431
DOI: 10.64898/2026.01.05.697685

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting TCR-pMHC Binding by Reinforcement LearningDOI 10.64898/2026.01.05.697685Read

TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-xbinding analysesSemantic proximity Read

A unified deep framework for peptide–major histocompatibility complex–T cell receptor binding predictionSemantic proximity Read

THLANet: A Deep Learning Framework for Predicting TCR-pHLA Binding in Immunotherapy ApplicationsSemantic proximity Read

EpicPred: predicting phenotypes driven by epitope-binding TCRs using attention-based multiple instance learningSemantic proximity Read

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifsSemantic proximity Read

A structure-informed deep learning framework for modeling TCR-peptide-HLA interactionsSemantic proximity Read

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifsSemantic proximity Read

Reusability Report: Meta-Learning for Antigen-Specific T-Cell Receptor Binder IdentificationSemantic proximity Read

Structure modeling and specificity of peptide-MHC class I interactions using geometric deep learningSemantic proximity Read

Predicting recognition between T cell receptors and epitopes using contextualized motifsSemantic proximity Read

EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddingsSemantic proximity Read

Deep learning pan-specific model for interpretable MHC-I peptide binding prediction with improved attention mechanism.Semantic proximity Read