ArticleGenome research2023
A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls.
Article in Genome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026Review
- 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
- Machine learning in AIRR diagnostics: Advances and applications.Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Enhancing sequence alignment of adaptive immune receptors through multi-task deep learning.Nucleic acids research · 2025Article
- Disease diagnostics using machine learning of B cell and T cell receptor sequences.Science (New York, N.Y.) · 2025Article
- Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning.Nucleic acids research · 2025Article
- An unbiased comparison of immunoglobulin sequence aligners.Briefings in bioinformatics · 2024Article
- Establishing a machine learning model based on dual-energy CT enterography to evaluate Crohn's disease activity.Insights into imaging · 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
- Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.Frontiers in immunology · 2023Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Crohn's disease (CD) is a chronic relapsing-remitting inflammatory disorder of the gastrointestinal tract that is characterized by altered innate and adaptive immune function. Although massively parallel sequencing studies of the T cell receptor repertoire identified oligoclonal expansion of unique clones, much less is known about the B cell receptor (BCR) repertoire in CD. Here, we present a novel BCR repertoire sequencing data set from ileal biopsies from pediatric patients with CD and controls, and identify CD-specific somatic hypermutation (SHM) patterns, revealed by a machine learning (ML) algorithm trained on BCR repertoire sequences. Moreover, ML classification of a different data set from blood samples of adults with CD versus controls identified that V gene usage, clusters, or mutation frequencies yielded excellent results in classifying the disease (F1 > 90%). In summary, we show that an ML algorithm enables the classification of CD based on unique BCR repertoire features with high accuracy.
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