DeepMind precomputed every possible one-letter mutation in the human genome
Google DeepMind released AlphaGenome Atlas on September 8. The database contains model predictions for about nine billion possible single-letter changes across the human genome. DeepMind says the data occupies about one petabyte and covers both protein-coding DNA and the much larger noncoding portion that helps regulate genes. Researchers can search the atlas without running the model themselves. DeepMind also released one score that ranks each variant by its predicted biological effect. Access is free for noncommercial research.
Verified 2:39 AM PDT · 3 original sources
The atlas contains predictions, not nine billion lab results. DeepMind says collaborators validated selected examples, but the company also states that AlphaGenome is not approved for clinical use. Nature quoted outside researchers who called the resource useful while warning that experiments and patient details still matter. A single impact score can help rank variants, but it can also hide which model assumption drove the ranking.
Rare-disease teams need to report whether the atlas finds causes that standard tools missed. Experiments then need to confirm those candidates. False-positive rates across different populations, independent comparisons with other models and the rules for commercial access will also matter. Clinical use still requires separate validation and regulatory review.
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