STAT+: DeepMind releases AlphaGenome source code, aiming to improve its AI predictions of gene regulation
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When the world\u2019s scientists finally pieced together a first draft of the human genome in 2003, one of the biggest surprises was just how little of it \u2014 only about 20,000 genes \u2014 are involved in the business of producing proteins. At first, the remaining 98% appeared not to do much of anything at all. With better tools, researchers began to discover that this \u201cjunk DNA\u201d actually exerts a tremendous amount of influence on how and where and when protein-coding genes get expressed. But more than two decades later, making sense of these complicated interactions \u2014 and how they contribute to disease \u2014 remains one of biology\u2019s most perplexing puzzles.\u00a0<\/p>\n
Now, a growing number of researchers are turning to an artificial intelligence developed by Google\u2019s AI research company DeepMind to predict how DNA encodes gene regulation, with an eye toward possible applications in therapeutic development. The model, called AlphaGenome, was first described in a preprint and blog post<\/a> last June. At the time, DeepMind\u2019s vice president of science, Pushmeet Kohli, called it a step toward understanding the \u201csemantics of DNA,<\/a>\u201d but far from a complete solution.\u00a0<\/p>\n Since its launch seven months ago, nearly 3,000 scientists from 160 countries have started using it to advance research into cancer, neurodegenerative disorders, and infectious diseases, Kohli told reporters at a press briefing Tuesday. Initially, the company limited the use of AlphaGenome to researchers doing noncommercial work, who could only access the model through DeepMind\u2019s servers via a free API. With its growing user base, Kohli said AlphaGenome currently has an API call volume of about 1 million per day.\u00a0<\/p>\n Continue to STAT+ to read the full story\u2026<\/a><\/p>\n<\/div>\n