What it is
AlphaMissense scores the pathogenicity of missense variants — single amino-acid changes — across the human proteome, classifying millions as likely benign or harmful. It fuses structural context from AlphaFold with population-genetics signal to help interpret genetic variation.
Evidence trail
BioAtlas keeps the path from source to decision visible. A connection records provenance; it does not imply that evidence is sufficient for every context.
Model passport
How AlphaMissense represents biology
Category is navigation. These fields describe the model-specific computational transformation and deliberately override broad category defaults.
Biological scale
Modalities & tasks
Registry, claims and frontier intelligence
Version history not yet curated
1 version record · release year not yet normalized. Model-family identity remains separate from capability and access changes.
Explore version lineage →0 normalized claims
No task, dataset, split and metric claim has been normalized for this record yet.
Open claim intelligence →1 connected frontier
Regulatory genome · Peer-reviewed capability
Inspect research horizon →Connected research frontiers
These records describe active research directions, not guaranteed capabilities of this model. Evidence stages and unresolved questions are preserved separately.
Million-base regulatory variant prediction
Google DeepMind · 2026-01-28Can a single model predict how coding and non-coding variants alter expression, splicing, chromatin and regulatory binding over long genomic context?
Evidence boundary and unresolved questions
The model is a research predictor, not a personal-genome or clinical diagnostic system; tissue specificity and very long-range enhancer logic remain limitations.
- How reliably do predictions transfer to rare cell states and patient contexts?
- Can causal mechanisms be separated from learned correlations?
- How should predictions be prospectively validated?
regulatory genomics · variant effects · non-coding DNA · splicingOpen frontier record →Inputs and outputs
Inputs
DNA sequenceOutputs
Sequence predictionsEmbeddings or generated sequenceScientific and technical profile
Scientific principles
Technology
Scientific lineage
These are transparent concept matches—not claims that one scientist alone caused this model. Each connection is based on the model’s recorded domain, scientific principles, technical terms or an explicit lineage link.
DNA as the hereditary transforming principle
Oswald Avery, Colin MacLeod & Maclyn McCartyGenomics, variant interpretation, gene therapy and sequence foundation models depend on DNA being the durable molecular carrier of biological information.
X-ray evidence for the helical structure of DNA
Rosalind Franklin & Raymond GoslingStructural genomics and sequence-to-structure reasoning began with experimentally grounded molecular geometry.
The DNA double helix and complementary base pairing
James Watson & Francis CrickSequence analysis, variant prediction, genome design and nucleic-acid therapeutics all rest on this structural logic.
Reading the sequences of proteins and DNA
Frederick SangerBiological foundation models exist because proteins and genomes became readable, comparable and computable at scale.
The central dogma and directional information transfer
Francis CrickMulti-omic models and sequence foundation models connect genotype, transcript and protein through this information-flow framework.
Anfinsen’s dogma—the thermodynamic hypothesis
Christian B. AnfinsenProtein structure prediction, inverse folding and generative protein design all assume that sequence strongly constrains structure and function.
Evaluation evidence
BioAtlas has not yet extracted a structured benchmark claim for this record.
Known limitations
- Performance depends on the evaluation dataset and operating conditions.
- A structured benchmark claim has not yet been extracted for this record.
- Outputs require task-specific scientific and experimental validation.
Milestones
Classified ~71M possible human missense variants.
Complements AlphaGenome on the coding genome.