MPGNN-DSA: A Meta-path-based Graph Neural Network for drug-side effect association prediction

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成果类型：

会议论文

作者：

Wenjie Yao;Weizhong Zhao;Xingpeng Jiang;Xianjun Shen;Tingting He

作者机构：

Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, Hubei, China

School of Computer, Central China Normal University,Wuhan, Hubei, Hubei, China

National Language Resources Monitoring and Research Center for Network Media, Central China Normal University, Wuhan, Hubei, China

[Wenjie Yao] Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, Hubei, China<&wdkj&>School of Computer, Central China Normal University,Wuhan, Hubei, Hubei, China

[Weizhong Zhao; Xingpeng Jiang; Xianjun Shen; Tingting He] Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, Hubei, China<&wdkj&>School of Computer, Central China Normal University,Wuhan, Hubei, Hubei, China<&wdkj&>National Language Resources Monitoring and Research Center for Network Media, Central China Normal University, Wuhan, Hubei, China

语种：

英文

关键词：

drug-side effect association prediction;meta-path;heterogeneous information network

年：

2022

页码：

627-632

会议名称：

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议论文集名称：

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议时间：

06 December 2022

会议地点：

Las Vegas, NV, USA

出版者：

IEEE

ISBN：

978-1-6654-6820-6

DOI：

10.1109/BIBM55620.2022.9995486

基金类别：

10.13039/501100001809-National Natural Science Foundation of China 10.13039/100006190-Research and Development

机构署名：

本校为第一机构

院系归属：

计算机学院

摘要：

Drug side effect is an important entity in the biomedical field, and identifying the association of the drug-side effects is a very important issue in pharmacological studies and drug risk-benefit. Traditional side effect discovery methods are mainly based on pharmacological experiments. These methods can detect the side effects of some drugs, but the identification process is time-consuming, expensive, and fails to identify some rare side effects. In recent years, with the expansion of massive biomedical data, computational-based methods are widely developed and applied for the task of drug-s...

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MPGNN-DSA: A Meta-path-based Graph Neural Network for drug-side effect association prediction

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