.png){kind=icon}
.png){kind=icon}
Return
Protein matchmaking through representation learning
.png){kind=icon}
OA
AI
DOI：10.1016/j.cels.2021.09.007.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Sledzieski, Singh, Cowen, and Berger employ representation learning to predict protein interactions and associations, additionally identifying binding residues between protein pairs. Generalizability is showcased by training on one organism while evaluating on others. The work exemplifies how transfer of AI-learned representations can advance knowledge in molecular biology.