Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Alexander W. Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason J. Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus
The paper trains a deep language model on 250 million protein sequences to learn biological representations that capture structural and functional properties.
Proceedings of the National Academy of Sciences · Apr 5, 2021Peer-reviewedSynthetic Biology