Google DeepMind released AlphaGenome Atlas, a web and API resource that provides precomputed predictions for the molecular effects of human single-nucleotide variants along with an AlphaGenome Variant Impact (AVI) score and attribution breakdowns. It covers roughly 9 billion possible single-letter DNA changes and is built from a 1-petabyte set of stored model outputs. Instead of rerunning the AlphaGenome model for each candidate variant, researchers can query the precomputed results (non-commercial now; commercial access is listed as coming soon).
AlphaGenome Atlas launches today as a Google DeepMind AI-powered map of how human DNA mutations may affect biology. It includes precomputed predictions for 9 billion possible single-letter DNA changes in a 1-petabyte dataset. Researchers can now explore and prioritize variants through a free web interface, with API access for deeper work.
AlphaGenome Atlas, from Google DeepMind, released precomputed AI predictions covering the effects of 9 billion single-nucleotide DNA variants across the human genome.
Google DeepMind announced and publicly released the AlphaGenome Atlas, a web repository of pre-computed AlphaGenome predictions for human DNA variants. The atlas includes predictions for 9 billion possible single-letter changes to a reference human genome. Researchers can now look up variant effects via the site—without running AlphaGenome code—and use a single-number impact score to prioritize experiments, though the predictions have limits like a 1 million base-pair input window.
Google DeepMind unveiled AlphaGenome Atlas, an AI tool aimed at helping researchers decode the human genome and biology. It includes a predictive map of every possible DNA letter change, with the human genome containing roughly 3 billion letter pairs. This is expected to accelerate scientific research and potentially enable new treatments for diseases.
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