ArticleNature genetics2023
Genome-wide prediction of disease variant effects with a deep protein language model.
Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 251 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
251 citing papers in PubMed, 1 synthesis or guideline pooled it, 411 citations in OpenAlex.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
- Regulated degradation of KCC2, a potassium-chloride co-transporter required for synaptic transmission and neurodevelopment.Channels (Austin, Tex.) · 2026Review
- Homology-Based Variant-Effect Predictors Break Down on Cytochrome P450 Pharmacogenes.bioRxiv : the preprint server for biology · 2026Article
- From Pathogenicity to Mechanism: A Variant Interpretation Framework for Monogenic Epilepsy.Clinical genetics · 2026Article
- Translating functional molecular knowledge into crop-breeding success.Nature reviews. Genetics · 2026Review
- The GPCRDiabetologia · 2026Article
- Probabilistic mapping of sub-genic intolerance reveals functional and disease-critical protein regions.bioRxiv : the preprint server for biology · 2026Article
- EmmaEmb: A quantitative framework for analyzing embedding spaces in molecular biology.Patterns (New York, N.Y.) · 2026Article
- Article
- PlantCAD2: A DNA foundation model for interpreting genomes across flowering plants.Cell genomics · 2026Article
- Unraveling the Genetic Basis of Cold Tolerance in Peanut (Plants (Basel, Switzerland) · 2026Article
- Systematic and proactive evaluation of AIRE missense variant effects.American journal of human genetics · 2026Article
- Unsupervised discovery of functional sequence patterns from protein language model with MotifAE.Nature communications · 2026Article
- Prediction of human missense variant effects from functional evidence.Nature genetics · 2026Article
- Characterization of putative germline pathogenic variants in 27 candidate cancer-predisposing genes in 813 cats using a feline-specific multiplex targeted sequencing.Scientific reports · 2026Article
- Deep Contrastive Learning for High-Throughput Prediction of Drug Resistance Mutations from Sequences.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- CATVariant: a web server for integrated protein variant interpretation across sequence, structure, population, and clinical evidence.Nucleic acids research · 2026Article
- Molecular dynamics simulations of intrinsically disordered protein regions enable biophysical interpretation of variant-effect predictors.HGG advances · 2026Article
- Decoding variants of uncertain significance in systemic autoinflammatory diseases.Nature reviews. Rheumatology · 2026Review
- Defining the molecular tolerance-to-damage landscape of SMARCA4 helicase genetic alterations.bioRxiv : the preprint server for biology · 2026Article
191 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.
Indexed as
Identifiers
What Socratic holds
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.