ArticleScience advances2021
A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity.
Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed, 110 citations in OpenAlex.
- Predicting specificity of TCR-pMHC interactions using machine-learning and biophysical models.Cell systems · 2026Article
- Single-cell analysis of adaptive NK and CMV-specific T-cell dynamics after allogeneic HSCT.Blood advances · 2026Article
- TcrDesign: de novo design of epitope-specific full-length T cell receptors.Science China. Life sciences · 2026Article
- The challenge and promise of studying human antigen-specific T cells.Nature reviews. Immunology · 2026Review
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- A comparative and exploratory analysis of computational methods for TCR structural prediction and antigen-specific TCR discovery.Briefings in bioinformatics · 2026Article
- Mitigating negative data bias to enhance TCR-epitope binding and residue interaction prediction.Briefings in bioinformatics · 2026Article
- Modeling TCR-Epitope Recognition Specificity: What We Should Learn to Succeed.Immunological reviews · 2026Review
- Biophysical modeling for accurate T cell specificity prediction of viral and tumor antigens.Nature communications · 2026Article
- Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026Article
- General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3.bioRxiv : the preprint server for biology · 2026Article
- TCRBinder: Unified pre-trained language model with paired-chain synergy for predicting T-cell receptor binding specificity.PLoS computational biology · 2026Article
- TCRdesign: an antigen-specific generative language model for de novo design of T-cell receptors.Briefings in bioinformatics · 2025Article
- Is the vaccination-induced B cell receptor repertoire predictable?Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database.Cell systems · 2025Article
- Characterization of human CMV-specific CD8Cell reports methods · 2025Article
- A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight.Briefings in bioinformatics · 2025Review
- Phage display enables machine learning discovery of cancer antigen-specific TCRs.Science advances · 2025Article
- TRAP: a contrastive learning-enhanced framework for robust TCR-pMHC binding prediction with improved generalizability.Chemical science · 2025Article
- Identifying T cell antigen at the atomic level with graph convolutional network.Nature communications · 2025Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring.
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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.