Get the latest tech news
AlphaGenome: AI for Better Understanding the Genome
Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to shed new light on genome function — now available via API.
Training data was sourced from large public consortia including ENCODE, GTEx, 4D Nucleome and FANTOM5, which experimentally measured these properties covering important modalities of gene regulation across hundreds of human and mouse cell types and tissues. This work was done thanks to the contributions of the AlphaGenome co-authors: Žiga Avsec, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, Lauren Nicolaisen, Eirini Arvaniti, Joshua Pan, Raina Thomas, Vincent Dutordoir, Matteo Perino, Soham De, Alexander Karollus, Adam Gayoso, Toby Sargeant, Anne Mottram, Lai Hong Wong, Pavol Drotár, Adam Kosiorek, Andrew Senior, Richard Tanburn, Taylor Applebaum, Souradeep Basu, Demis Hassabis and Pushmeet Kohli. We would also like to thank Dhavanthi Hariharan, Charlie Taylor, Ottavia Bertolli, Yannis Assael, Alex Botev, Anna Trostanetski, Lucas Tenório, Victoria Johnston, Richard Green, Kathryn Tunyasuvunakool, Molly Beck, Uchechi Okereke, Rachael Tremlett, Sarah Chakera, Ibrahim I. Taskiran, Andreea-Alexandra Muşat, Raiyan Khan, Ren Yi and the greater Google DeepMind team for their support, help and feedback.
Or read this on Hacker News