ArticleBriefings in bioinformatics2024
TCR clustering by contrastive learning on antigen specificity.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- The Role of the T Cell Receptor Sequence in Shaping T Cell Functional Fate.Immunological reviews · 2026Review
- The challenge and promise of studying human antigen-specific T cells.Nature reviews. Immunology · 2026Review
- Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.Journal for immunotherapy of cancer · 2026Review
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- Protein language models accurately predict polymorphic peptide-modulated NK cell receptor-HLA class I interaction strengths.Science advances · 2026Article
- TCR representation learning with protein language models: a comprehensive review.International immunology · 2026Review
- Disrupting explicit encoding paradigms: property-interactive transformers decode T-cell receptor specificity beyond dataset biases.Briefings in bioinformatics · 2025Article
- Quantitative and large-scale investigation of human TCR-HLA cross-reactivity.Science advances · 2025Article
- Origins of T-cell-mediated autoimmunity in acquired aplastic anaemia.British journal of haematology · 2025Review
- Targeting cancer with precision: strategical insights into TCR-engineered T cell therapies.Theranostics · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Effective clustering of T-cell receptor (TCR) sequences could be used to predict their antigen-specificities. TCRs with highly dissimilar sequences can bind to the same antigen, thus making their clustering into a common antigen group a central challenge. Here, we develop TouCAN, a method that relies on contrastive learning and pretrained protein language models to perform TCR sequence clustering and antigen-specificity predictions. Following training, TouCAN demonstrates the ability to cluster highly dissimilar TCRs into common antigen groups. Additionally, TouCAN demonstrates TCR clustering performance and antigen-specificity predictions comparable to other leading methods in the field.
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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.