MR2CPPIS: Accurate prediction of protein–protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism

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成果类型：

期刊论文

作者：

Gong, Yinyin;Li, Rui;Liu, Yan;Wang, Jilong;Cao, Buwen;...

通讯作者：

Rui Li

作者机构：

[Liu, Yan; Li, Rui; Li, Renfa; Fu, Xiangzheng; Gong, Yinyin] College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

[Liu, Yan; Li, Renfa; Gong, Yinyin] Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems, Hunan University, Changsha, 410082, China

[Li, Rui] Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems, Hunan University, Changsha, 410082, China. Electronic address: rui@hnu.edu.cn

[Wang, Jilong] Peng Cheng Laboratory, Shenzhen, 518066, China

[Cao, Buwen] College of Information and Electronic Engineering, Hunan City University, Yiyang, 413002, China

通讯机构：

[Rui Li] C

College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China<&wdkj&>Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems, Hunan University, Changsha, 410082, China

语种：

英文

关键词：

Coordinate attention;Multi-scale;PPI sites prediction;Res2Net;Sequence-based method

期刊：

Computers in Biology and Medicine

ISSN：

0010-4825

年：

2024

卷：

176

页码：

108543

DOI：

10.1016/j.compbiomed.2024.108543

基金类别：

CRediT authorship contribution statement Yinyin Gong: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Rui Li: Writing – review & editing, acquisition, Formal analysis, Data curation, Conceptualization. Yan Liu: Visualization, Validation, Supervision, Resources, Project administration, Data curation, Conceptualization. Jilong Wang: Visualization, Software, Methodology, Investigation, Conceptualization. Buwen Cao: Software, Resources, Project

机构署名：

本校为其他机构

院系归属：

信息与电子工程学院

摘要：

Proteins play a vital role in various biological processes and achieve their functions through protein-protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological methods for identifying PPIs are costly, labor-intensive, and time-consuming. The development of computational prediction methods for PPI sites offers promising alternatives. Most known deep learning (DL) methods employ layer-wise multi-scale CNNs to extract features from protein sequences. But, these methods usually neglect the spatial positions and hierarchical information embedded w...

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MR2CPPIS: Accurate prediction of protein–protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism

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