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AlphaGenome (Google DeepMind)

high confidence · updated 2026-06-06

Google DeepMind's regulatory-variant-effect prediction model for human-genome analysis; published in Nature January 2026.

AlphaGenome is an AI model developed by Google DeepMind for predicting the effects of genetic variants on gene regulation in the human genome. It was published in Nature on January 28, 2026, and continues the pattern, established by the AlphaFold family, of DeepMind applying frontier AI to problems in biology.

Publication

The model was described in "Advancing regulatory variant effect prediction with AlphaGenome," published in Nature on January 28, 2026. The New York Times covered the release the same day under the headline "With AlphaGenome, Researchers Are Using A.I. to Decode the Human Blueprint."

AlphaGenome extends a sequence of DeepMind biology models: AlphaFold (AlphaFold (DeepMind)) for protein structure prediction, AlphaFold 3 for molecular complexes, and AlphaGenome for genome regulation. The 2024 Nobel Prize in Chemistry was awarded for AlphaFold, cited as an example of AI applied to scientific problems. Demis Hassabis leads DeepMind's work in this area, and the broader vision of AI-accelerated biology is set out in Machines of Loving Grace (Amodei's biology vision).

The model is relevant to AI Biosecurity as a dual-use concern and to AI for Science.

Relationships

Sources

  • Nature / Advancing regulatory variant effect prediction with AlphaGenome (2026-01-28)
  • NYT / With AlphaGenome, Researchers Are Using A.I. to Decode the Human Blueprint (2026-01-28)