ArticlePLoS computational biology2024
Large scale paired antibody language models.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Tokenizing loops of antibodies.mAbs · 2026Article
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- IMGT-NC Engineered Variants of INN Therapeutic IG or Antibodies and Related IgSF Proteins (TR, FPIA and CPCA): Bridging Sequences, Structures and Functions for AI.Biomolecules · 2026Review
- H3BERTa: A CDR-H3-specific language model for antibody repertoire analysis.Patterns (New York, N.Y.) · 2026Article
- Evidence-aware comparison of sequence-centric machine learning for antibody discovery and optimization.Briefings in bioinformatics · 2026Article
- AbTune: layer-wise selective fine-tuning of protein language models for antibodies.Briefings in bioinformatics · 2026Article
- VDJ-REMIX: REpertoire Module Identification and eXploration.Bioinformatics (Oxford, England) · 2026Article
- Article
- Evaluating Expert Specialization in Mixture-of-Experts Antibody Language Models.bioRxiv : the preprint server for biology · 2026Article
- IMGTAntibodies (Basel, Switzerland) · 2026Review
- Article
- Contrastive learning enables epitope overlap predictions for targeted antibody discovery.Patterns (New York, N.Y.) · 2026Article
- Protein Language Models: Applications and Perspectives.Journal of proteome research · 2026Review
- Paraplume: A fast and accurate antibody paratope prediction method provides insights into repertoire-scale binding dynamics.PLoS computational biology · 2026Article
- Deep generative modeling captures maturation-dependent pairing patterns in human antibodies.iScience · 2026Article
- Learning the language of protein-protein interactions.Nature communications · 2026Article
- CoV-UniBind: a unified antibody binding database for SARS-CoV-2.Bioinformatics advances · 2026Article
- AI-driven discovery in protein science for immunology and infectious disease research.Frontiers in bioinformatics · 2026Review
- Ensemble molecular mimicry correlates with antibody cross-reactivity in proteome-wide studies.Frontiers in immunology · 2026Article
- Prodigy protein: Python package for zero-shot protein engineering using protein language models.BMC bioinformatics · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antibodies are proteins produced by the immune system that can identify and neutralise a wide variety of antigens with high specificity and affinity, and constitute the most successful class of biotherapeutics. With the advent of next-generation sequencing, billions of antibody sequences have been collected in recent years, though their application in the design of better therapeutics has been constrained by the sheer volume and complexity of the data. To address this challenge, we present IgBert and IgT5, the best performing antibody-specific language models developed to date which can consistently handle both paired and unpaired variable region sequences as input. These models are trained comprehensively using the more than two billion unpaired sequences and two million paired sequences of light and heavy chains present in the Observed Antibody Space dataset. We show that our models outperform existing antibody and protein language models on a diverse range of design and regression tasks relevant to antibody engineering. This advancement marks a significant leap forward in leveraging machine learning, large scale data sets and high-performance computing for enhancing antibody design for therapeutic development.
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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.