ArticleProceedings of the National Academy of Sciences of the United States of America2024
Computational detection of antigen-specific B cell receptors following immunization.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Heavy-chain immune repertoire sequencing enables language-model prediction of antigen-specific antibodies.Research square · 2026Article
- Medical software for precision diagnostics of infection with immunoprofiling and artificial intelligence.Journal of translational medicine · 2026Review
- LM-QASAS: reference-free identification of antigen-specific sequences from the BCR repertoire using antibody language models.Frontiers in immunology · 2026Article
- Germline based SARS-CoV-2 specific B cell repertoire motif identified with novel sequence based bioinformatic pipeline.Frontiers in immunology · 2026Article
- B cells and B-cell receptor repertoire features in coronary heart disease: immunopathogenic roles, clinical relevance, and therapeutic potential.Frontiers in cardiovascular medicine · 2026Review
- Optimizing the breadth of SARS-CoV-2-neutralizing antibodies in vivo and in silico.Human vaccines & immunotherapeutics · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and SARS-CoV-2 infections. We show that different lineages converge to the same responding Complementarity Determining Region 3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.
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Registered trials
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