ArticleiScience2026
Computational identification of antigen-specific T cell groups through generative epitope modeling.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Single-cell T cell receptor (TCR) sequencing enables high-resolution analysis of TCR diversity and clonal expansion. However, inferring antigen specificity for individual TCRs remains challenging and typically requires costly functional assays. We introduce EpitopeGen, a transformer-based model that generates candidate epitope sequences from TCR sequences, enabling population-level identification of T cell groups with shared predicted antigen specificity. EpitopeGen employs a semi-supervised strategy that searches over 70 billion candidate TCR-epitope pairs and incorporates high-confidence binding predictions as pseudo-labels under biologically inspired quality control. Generated epitopes exhibit high predicted binding probabilities, sequence diversity, realistic biochemical properties, and biophysical stability. In cancer datasets, EpitopeGen identifies clonally expanded tumor-infiltrating CD8
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