The TCR Motif Atlas: a database of specificities for TCRs recognizing viral, cancer, and autoimmune epitopes
- 1Department of Fundamental Oncology, UNIL, Ludwig Institute for Cancer Research, University of Lausanne , Bugnon 25A, 1011 Lausanne ,
- 2Swiss Institute of Bioinformatics (SIB) , 1015 Lausanne ,
- 3Agora Cancer Research Centre , 1011 Lausanne ,
Abstract
T-cell recognition is elicited by the binding between T-cell receptors (TCRs) and epitopes. Many machine learning approaches have been proposed to model TCR–epitope recognition specificity, but most of them act as black boxes. To visualize TCR–epitope recognition specificity, we developed the TCR Motif Atlas (https://tcrmotifatlas.unil.ch). This database builds upon the probabilistic framework of TCR specificity profiles (TSPs) to visualize V and J genes as well as complementarity-determining Region 3 (CDR3) lengths and amino acids enriched in epitope-specific TCRs with respect to baseline TCR repertoires for hundreds of epitopes. An interactive interface enables users to build TSPs based on their own set of TCR sequences to investigate epitope recognition specificity or to explore potential biases in TCR repertoires of known or undetermined specificity. The TCR Motif Atlas further provides links to curated compilations of epitope-specific TCRs and crystal structures of TCR–epitope complexes.
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BibTeX
@article{tadros2026motif,
title = {{The TCR Motif Atlas: a database of specificities for TCRs recognizing viral, cancer, and autoimmune epitopes}},
author = {Daniel M Tadros and Aisha Shah and Rita Ann Roessner and Julien Racle and David Gfeller},
journal = {Nucleic Acids Research},
year = {2026},
month = nov,
doi = {10.1093/nar/gkag1095},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1095/9006191},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - The TCR Motif Atlas: a database of specificities for TCRs recognizing viral, cancer, and autoimmune epitopes
AU - Daniel M Tadros
AU - Aisha Shah
AU - Rita Ann Roessner
AU - Julien Racle
AU - David Gfeller
PY - 2026
DA - 2026/11/02
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1095
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1095/9006191
AB - T-cell recognition is elicited by the binding between T-cell receptors (TCRs) and epitopes. Many machine learning approaches have been proposed to model TCR–epitope recognition specificity, but most of them act as black boxes. To visualize TCR–epitope recognition specificity, we developed the TCR Motif Atlas (https://tcrmotifatlas.unil.ch). This database builds upon the probabilistic framework of TCR specificity profiles (TSPs) to visualize V and J genes as well as complementarity-determining Region 3 (CDR3) lengths and amino acids enriched in epitope-specific TCRs with respect to baseline TCR repertoires for hundreds of epitopes. An interactive interface enables users to build TSPs based on their own set of TCR sequences to investigate epitope recognition specificity or to explore potential biases in TCR repertoires of known or undetermined specificity. The TCR Motif Atlas further provides links to curated compilations of epitope-specific TCRs and crystal structures of TCR–epitope complexes.
SN - 0305-1048
SN - 1362-4962
ER -