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Attribute
Genomics & Sequence Modeling

AlphaMissense

Google DeepMind
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CategoryGenomics & Sequence Modeling
CompanyGoogle DeepMind
PriceFree Open Access
StatusStatus not confirmed
AvailabilityAvailable on GitHub and Ensembl / ClinVar cross-references
Last checked20/09/2026
FeaturesComprehensive 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
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)