ArticleNature methods2026
ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains.
Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- B-Cell Aware Analysis of Single-Cell Transcriptomics Data.Methods in molecular biology (Clifton, N.J.) · 2027Article
- A Synthetic Platform for Antibody Junctional Diversification Beyond Natural Constraints.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- AbTune: layer-wise selective fine-tuning of protein language models for antibodies.Briefings in bioinformatics · 2026Article
- Deep generative modeling captures maturation-dependent pairing patterns in human antibodies.iScience · 2026Article
- Germline-aware deep learning models and benchmarks for predicting antibody VH-VL pairing.mAbs · 2025Article
- Data-optimal scaling of paired antibody language models.bioRxiv : the preprint server for biology · 2025Article
- A Single-Cell Atlas of Transcriptional and Immunoglobulin Repertoire Evolution in Early B Cell Development.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The development of stable antibodies formed by compatible heavy (H) and light (L) chain pairs is crucial in both in vivo maturation of antibody-producing cells and ex vivo designs of therapeutic antibodies. We present ImmunoMatch, a machine-learning framework trained on paired H and L sequences from human B cells to identify molecular features underlying chain compatibility. ImmunoMatch distinguishes cognate from random H-L pairs and captures differences associated with κ and λ light chains, reflecting B cell selection mechanisms in the bone marrow. We apply ImmunoMatch to reconstruct paired antibodies from spatial VDJ sequencing data and study the refinement of H-L pairing across B cell maturation stages in health and disease. We find further that ImmunoMatch is sensitive to sequence differences at the H-L interface. These insights provide a computational lens into the broader biological principles governing antibody assembly and stability.
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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 Socratic graph.