Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences

Alexander Rives
Alexander Rives
Siddharth Goyal
Siddharth Goyal
Joshua Meier
Joshua Meier
Demi Guo
Demi Guo
Jerry Ma
Jerry Ma

bioRxiv, pp. 622803-31, 2019.

Cited by: 11|Bibtex|Views104|DOI:https://doi.org/10.1101/622803
Other Links: academic.microsoft.com

Abstract:

In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In biology, the anticipated growth of sequencing promises unprecedented data on natural sequence diversity. Learning the natural distri...More

Code:

Data:

Full Text
Your rating :
0

 

Tags
Comments