RGN: Residue-Based Graph Attention and Convolutional Network for Protein–Protein Interaction Site Prediction
Author:
Affiliation:
1. College of Computer Science and Technology, China University of Petroleum, QingDao266580, China
2. Department of Artificial Intelligence, Faculty of Computer Science, Polytechnical University of Madrid, Madrid28031, Spain
Funder
Ministry of Science and Technology of the People's Republic of China
Taishan Scholar Project of Shandong Province
Central University Basic Research Fund of China
National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c01092
Reference29 articles.
1. Protein–protein interaction site prediction through combining local and global features with deep neural networks
2. Algorithmic approaches to protein-protein interaction site prediction
3. Protein–protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique
4. Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory network
5. DELPHI: accurate deep ensemble model for protein interaction sites prediction
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