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Genomics & Bioinformatics · Clinical Variant Effect Prediction

AlphaMissense

By Google DeepMind →

Catalog of 71 million human missense mutations classified for clinical pathogenicity

AlphaMissense adapts AlphaFold to predict the clinical pathogenicity of all 71 million possible human single amino acid substitutions, categorizing 89% of variants with high confidence.

Comprehensive predictions for all 71 million possible human missense variantsTrained on population frequency data and structural context without clinical label leakageClassified 89% of missense variants as either likely pathogenic (32%) or likely benign (57%)Pre-computed database and downloadable BigWig/VCF files for integration into clinical pipelines
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Overview

AlphaMissense adapts AlphaFold to predict the clinical pathogenicity of all 71 million possible human single amino acid substitutions, categorizing 89% of variants with high confidence.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:09:40

Key Features

  • Comprehensive predictions for all 71 million possible human missense variants
  • Trained on population frequency data and structural context without clinical label leakage
  • Classified 89% of missense variants as either likely pathogenic (32%) or likely benign (57%)
  • Pre-computed database and downloadable BigWig/VCF files for integration into clinical pipelines

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
Rare disease diagnosis, oncogenic driver mutation identification, and human genetics
Research Workflow
Query missense variant (e.g. BRCA1 p.Cys61Gly) -> obtain pathogenicity score (0 to 1)
Compute & Hardware
Pre-computed lookup table (database) / GPU for novel sequences
Licensing & Academic Use
Creative Commons Attribution 4.0 (CC BY 4.0)
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing AlphaMissense in scientific publications and benchmark papers.

@software{alphamissense_2026,
  title = {{AlphaMissense}},
  author = {{Google DeepMind}},
  year = {2026},
  url = {https://github.com/google-deepmind/alphamissense},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for AlphaMissense.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeAI Model & Database
Access modeOpen Access
AI roleClinical Pathogenicity Classification
Input dataNot recorded
Output dataNot recorded
Licence conditionsCreative Commons Attribution 4.0 (CC BY 4.0)
Commercial eligibilityAvailable for research and non-commercial clinical evaluation
Compute requirementsPre-computed lookup table (database) / GPU for novel sequences
ValidationNot recorded
TypeStructural variant effect prediction model
Intended useNot recorded
CompatibilityNot recorded
ManufacturerGoogle DeepMind
Biological applicationRare disease diagnosis, oncogenic driver mutation identification, and human genetics
Research workflowQuery missense variant (e.g. BRCA1 p.Cys61Gly) -> obtain pathogenicity score (0 to 1)
Evidence levelPeer-reviewed research (Science 2023)
Integration evidencehttps://github.com/google-deepmind/alphamissense
Laboratory handoffInforms targeted functional genomics assays (Deep Mutational Scanning)
AvailabilityAvailable on GitHub and Ensembl / ClinVar cross-references
Price / accessFree Open Access

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for AlphaMissense yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

Available on GitHub and Ensembl / ClinVar cross-references

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating AlphaMissense.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5