ArticleCell genomics2025
Benchmarking of T cell receptor-epitope predictors with ePytope-TCR.
Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- T Cell Thoughts.Immunological reviews · 2026Review
- Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026Review
- The T Cell Receptor: Molecular Sensor, Therapeutic Mediator and Probabilistic Driver of Adaptive Immunity.Immunological reviews · 2026Review
- Modeling TCR-Epitope Recognition Specificity: What We Should Learn to Succeed.Immunological reviews · 2026Review
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026Article
- Comprehensive mapping of identical sequences across human proteins emphasizes the widespread issue of shared epitopes in self-antigens.NAR genomics and bioinformatics · 2026Article
- Turep: Detecting cross-cancer tumor-reactive T cells in single-cell and spatial transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- AMULETY: A Python package to embed adaptive immune receptor sequences.Immunoinformatics (Amsterdam, Netherlands) · 2026Article
- AI-driven computational methods and benchmarking for T-cell antigen identification.Briefings in bioinformatics · 2026Review
- HLA alleles shape distinct biases in the usage preferences of TCR VFrontiers in immunology · 2026Article
- AI-driven discovery in protein science for immunology and infectious disease research.Frontiers in bioinformatics · 2026Review
- Computational Methods in Immunoinformatics: Epitope Discovery and Diagnostic Applications.ACS omega · 2025Review
- T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database.Cell systems · 2025Article
- Predicting TCR-epitope recognition: How good are we?Cell genomics · 2025Article
- Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the recognition of disease-derived epitopes through T cell receptors (TCRs) has the potential to serve as a stepping stone for the development of efficient immunotherapies and vaccines. While a plethora of sequence-based prediction methods for TCR-epitope binding exists, their pre-trained models have not been comparatively evaluated. To alleviate this shortcoming, we integrated 21 TCR-epitope prediction models into the immune-prediction framework ePytope, offering interoperable interfaces with standard TCR repertoire data formats. We showcase the applicability of ePytope-TCR by evaluating the performance of these publicly available prediction models on two challenging datasets. While novel predictors successfully predicted binding to frequently observed epitopes, all methods failed for less frequently observed epitopes. Further, we detected a strong bias in the prediction scores between different epitope classes. We envision this benchmark to guide researchers in their choice of a predictor and to accelerate the method development by defining standardized evaluation settings.
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