# Google DeepMind's AlphaGenome Predicts DNA Function at Million-Base-Pair Scale

> Google DeepMind has released AlphaGenome, a model built to predict what stretches of DNA actually do. Where AlphaFold mapped how proteins fold, AlphaGenome targets the regulatory genome: it forecasts gene expression, DNA accessibility, transcription factor binding, and folding across spans of up to one million base pairs. Technically it predicts 5,930 human genome tracks at single-base resolution across 11 different output types, and it has been available to academic scientists since mid-2025. The appeal is scale and precision together, letting researchers ask how distant regulatory elements shape whether a gene switches on. There are real limits: it struggles to connect variants more than 100,000 base pairs apart, and it was trained only on human and mouse data. Most of the genome is not genes but the switches that control them, and that regulatory layer is where a lot of disease biology hides. A model that reads it at this resolution could speed up work that has been slow and expensive to do experimentally.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Chemistry World · Published Wednesday, August 19, 2026_

## Wortins' read

Google DeepMind has released AlphaGenome, a model built to predict what stretches of DNA actually do. Where AlphaFold mapped how proteins fold, AlphaGenome targets the regulatory genome: it forecasts gene expression, DNA accessibility, transcription factor binding, and folding across spans of up to one million base pairs. Technically it predicts 5,930 human genome tracks at single-base resolution across 11 different output types, and it has been available to academic scientists since mid-2025. The appeal is scale and precision together, letting researchers ask how distant regulatory elements shape whether a gene switches on. There are real limits: it struggles to connect variants more than 100,000 base pairs apart, and it was trained only on human and mouse data. Most of the genome is not genes but the switches that control them, and that regulatory layer is where a lot of disease biology hides. A model that reads it at this resolution could speed up work that has been slow and expensive to do experimentally.

## Source

[Read the full story at Chemistry World](https://www.chemistryworld.com/news/googles-alphagenome-wants-to-do-for-dna-what-alphafold-did-for-proteins/4022824.article)

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