GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction.
Ermal ElbasaniSoualihou Ngnamsie NjimbouomTae-Jin OhEung-Hee KimHyun LeeJeong-Dong KimPublished in: BMC bioinformatics (2022)
The performance of GCRNN is based on the classification accordiong to a binary class of interactions between proteins and compounds The architectural design of GCRNN model comes with the integration of the Bi-Recurrent layer on top of CNN to learn dependencies of motifs on protein sequences and improve the accuracy of the predictions.