ArticleFrontiers in immunology2023
Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 13 citations in OpenAlex.
- AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026Review
- Article
- The current landscape of adaptive immune receptor genomic and repertoire data: OGRDB and VDJbase.Nucleic acids research · 2026Article
- Germline based SARS-CoV-2 specific B cell repertoire motif identified with novel sequence based bioinformatic pipeline.Frontiers in immunology · 2026Article
- Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025Article
- Unique Features and Collateral Immune Effects of mRNA-LNP COVID-19 Vaccines: Plausible Mechanisms of Adverse Events and Complications.Pharmaceutics · 2025Review
- Enhancing sequence alignment of adaptive immune receptors through multi-task deep learning.Nucleic acids research · 2025Article
- An unbiased comparison of immunoglobulin sequence aligners.Briefings in bioinformatics · 2024Article
- bcRflow: a Nextflow pipeline for characterizing B cell receptor repertoires from non-targeted transcriptomic data.NAR genomics and bioinformatics · 2024Article
- nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.PLoS computational biology · 2024Article
- Guidelines for reproducible analysis of adaptive immune receptor repertoire sequencing data.Briefings in bioinformatics · 2024Article
- A novel approach to T-cell receptor beta chain (TCRB) repertoire encoding using lossless string compression.Bioinformatics (Oxford, England) · 2023Article
- A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls.Genome research · 2023Article
- Sarcoidosis-related autoimmune inflammation in COVID-19 convalescent patients.Frontiers in medicine · 2023Review
Corrections and comments
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Authors and funding
15 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance. Methods: We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls. Results: In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients. Discussion: These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.
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