ArticleNucleic acids research2018
TCRmodel: high resolution modeling of T cell receptors from sequence.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed, 68 citations in OpenAlex.
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- AutoEpiCollect 2.0: A Web-Based Machine Learning Tool for Personalized Peptide Cancer Vaccine Design.Molecules (Basel, Switzerland) · 2025Article
- A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight.Briefings in bioinformatics · 2025Review
- Nanobodies: From Discovery to AI-Driven Design.Biology · 2025Review
- LightCTL: lightweight contrastive TCR-pMHC specificity learning with context-aware prompt.Briefings in bioinformatics · 2025Article
- TRain: T-cell receptor automated immunoinformatics.BMC bioinformatics · 2025Article
- T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity.Communications biology · 2025Article
- A fingerprint approach to pioneer structure-based T cell receptor repertoire analysis and specificity prediction.Frontiers in immunology · 2025Article
- Predicting Antigen-Specificities of Orphan T Cell Receptors from Cancer Patients with TCRpcDist.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Nature methods · 2024Review
- AutoEpiCollect, a Novel Machine Learning-Based GUI Software for Vaccine Design: Application to Pan-Cancer Vaccine Design Targeting PIK3CA Neoantigens.Bioengineering (Basel, Switzerland) · 2024Article
- SARS-CoV-2 infection establishes a stable and age-independent CD8Nature communications · 2023Article
- Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.Journal of chemical theory and computation · 2023Review
- TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.Nucleic acids research · 2023Article
- Detection of mutant antigen-specific T cell receptors against multiple myeloma for T cell engineering.Molecular therapy. Methods & clinical development · 2023Article
- Neoantigen-specific CD8 T cells with high structural avidity preferentially reside in and eliminate tumors.Nature communications · 2023Article
- Entropic analysis of antigen-specific CDR3 domains identifies essential binding motifs shared by CDR3s with different antigen specificities.Cell systems · 2023Article
- Structural Modeling of Adaptive Immune Responses to Infection.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A current and future perspective on T cell receptor repertoire profiling.Frontiers in genetics · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
T cell receptors (TCRs), along with antibodies, are responsible for specific antigen recognition in the adaptive immune response, and millions of unique TCRs are estimated to be present in each individual. Understanding the structural basis of TCR targeting has implications in vaccine design, autoimmunity, as well as T cell therapies for cancer. Given advances in deep sequencing leading to immune repertoire-level TCR sequence data, fast and accurate modeling methods are needed to elucidate shared and unique 3D structural features of these molecules which lead to their antigen targeting and cross-reactivity. We developed a new algorithm in the program Rosetta to model TCRs from sequence, and implemented this functionality in a web server, TCRmodel. This web server provides an easy to use interface, and models are generated quickly that users can investigate in the browser and download. Benchmarking of this method using a set of nonredundant recently released TCR crystal structures shows that models are accurate and compare favorably to models from another available modeling method. This server enables the community to obtain insights into TCRs of interest, and can be combined with methods to model and design TCR recognition of antigens. The TCRmodel server is available at: http://tcrmodel.ibbr.umd.edu/.
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What OpenQuestion holds
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.