ArticleCell reports. Medicine2021
Use of machine learning to identify a T cell response to SARS-CoV-2.
Article in Cell reports. Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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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
26 citing papers in PubMed.
- Medical software for precision diagnostics of infection with immunoprofiling and artificial intelligence.Journal of translational medicine · 2026Review
- Evaluating the utility of amino acid similarity-aware kmers to represent TCR repertoires for classification.PLoS computational biology · 2026Article
- Sepsis reporting signals associated with endothelin receptor antagonists and IFITM3-Centered interferon-responsive monocyte features: a pharmacovigilance and transcriptomic study.Frontiers in pharmacology · 2026Article
- Challenges and future directions of AIRR-seq-based diagnostics.Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Article
- KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification.Frontiers in immunology · 2025Article
- The characterization of CD8Emerging microbes & infections · 2024Review
- Hepatitis E virus: from innate sensing to adaptive immune responses.Nature reviews. Gastroenterology & hepatology · 2024Review
- Seven-chain adaptive immune receptor repertoire analysis in rheumatoid arthritis reveals novel features associated with disease and clinically relevant phenotypes.Genome biology · 2024Article
- A quest for universal anti-SARS-CoV-2 T cell assay: systematic review, meta-analysis, and experimental validation.NPJ vaccines · 2024Article
- Entropic analysis of antigen-specific CDR3 domains identifies essential binding motifs shared by CDR3s with different antigen specificities.Cell systems · 2023Article
- Machine learning identifies T cell receptor repertoire signatures associated with COVID-19 severity.Communications biology · 2023Article
- Architecture of the SARS-CoV-2-specific T cell repertoire.Frontiers in immunology · 2023Review
- Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.Frontiers in immunology · 2023Article
- A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls.Genome research · 2023Article
- Clonal diversity predicts persistence of SARS-CoV-2 epitope-specific T-cell response.Communications biology · 2022Article
- Multiple high-regional-incidence cardiac disease diagnosis with deep learning and its potential to elevate cardiologist performance.iScience · 2022Article
- Article
- A new approach for determining SARS-CoV-2 epitopes using machine learning-based in silico methods.Computational biology and chemistry · 2022Article
- Understanding T cell responses to COVID-19 is essential for informing public health strategies.Science immunology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease (n = 17) and SARS-CoV-2 infection-naive (control) individuals (n = 39). Applying a machine learning approach to TCR beta (TRB) repertoire data, we can classify patient/control samples with a training sensitivity, specificity, and accuracy of 88.2%, 100%, and 96.4% and a testing sensitivity, specificity, and accuracy of 82.4%, 97.4%, and 92.9%, respectively. Interestingly, the same machine learning approach cannot separate SARS-CoV-2 recovered from SARS-CoV-2 infection-naive individual samples on the basis of B cell receptor (immunoglobulin heavy chain; IGH) repertoire data, suggesting that the T cell response to SARS-CoV-2 may be more stereotyped and longer lived. Following validation in larger cohorts, our method may be useful in detecting protective immunity acquired through natural infection or in determining the longevity of vaccine-induced immunity.
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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.