GraphDTA: Predicting drug-target binding affinity with graph neural networks
Thin Nguyen, Hang Le, Thomas P. Quinn, Tri Nguyen, Thuc Duy Le, Svetha Venkatesh
Representing drugs as molecular graphs, GraphDTA lowers drug-target affinity prediction error to MSE 0.229 on Davis and 0.139 on Kiba versus deep learning baselines.
Bioinformatics · Oct 15, 2020Peer-reviewedBioinformatics✦ In-depth digest