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GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction.

Ermal ElbasaniSoualihou Ngnamsie NjimbouomTae-Jin OhEung-Hee KimHyun LeeJeong-Dong Kim
Published 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.
Keyphrases
  • neural network
  • protein protein
  • machine learning
  • convolutional neural network
  • amino acid
  • deep learning
  • binding protein