ArticleImmunoinformatics (Amsterdam, Netherlands)2024
A comparison of clustering models for inference of T cell receptor antigen specificity.
Article in Immunoinformatics (Amsterdam, Netherlands), 2024. 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, 15 citations in OpenAlex.
- Machine Learning of Personal Repertoires From Public T Cell Receptors.Immunological reviews · 2026Review
- A cell-based kinetic framework enables TCR specificity prediction.Signal transduction and targeted therapy · 2026Article
- Deciphering antigen-driven T cell responses through vectorized TCRdist sequence neighborhood quantification.bioRxiv : the preprint server for biology · 2026Article
- Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding.ArXiv · 2026Article
- Article
- Evolution of the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones.Nature communications · 2026Article
- NeoTCRseek: an integrated platform for high-sensitivity identification of neoantigen-specific TCR clonotypes to track clinical T-cell dynamics.Frontiers in immunology · 2026Article
- Quantitative and large-scale investigation of human TCR-HLA cross-reactivity.Science advances · 2025Article
- Article
- T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database.Cell systems · 2025Article
- Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction.bioRxiv : the preprint server for biology · 2025Article
- The differential immunological impact of photon vs proton radiation therapy in high-grade lymphopenia in patients with gastrointestinal tumors.Clinical and experimental immunology · 2025Article
- Conditional generation of real antigen-specific T cell receptor sequences.Nature machine intelligence · 2025Article
- T cell receptor-centric perspective to multimodal single-cell data analysis.Science advances · 2024Article
- TCR clustering by contrastive learning on antigen specificity.Briefings in bioinformatics · 2024Article
- Designing meaningful continuous representations of T cell receptor sequences with deep generative models.Nature communications · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The vast potential sequence diversity of TCRs and their ligands has presented an historic barrier to computational prediction of TCR epitope specificity, a holy grail of quantitative immunology. One common approach is to cluster sequences together, on the assumption that similar receptors bind similar epitopes. Here, we provide the first independent evaluation of widely used clustering algorithms for TCR specificity inference, observing some variability in predictive performance between models, and marked differences in scalability. Despite these differences, we find that different algorithms produce clusters with high degrees of similarity for receptors recognising the same epitope. Our analysis strengthens the case for use of clustering models to identify signals of common specificity from large repertoires, whilst highlighting scope for improvement of complex models over simple comparators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.