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Improving drug–drug interactions prediction with interpretability via meta-path-based information fusion

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成果类型:
期刊论文
作者:
Zhao, Weizhong;Yuan, Xueling;Shen, Xianjun;Jiang, Xingpeng;Shi, Chuan;...
通讯作者:
Weizhong Zhao
作者机构:
[Shen, Xianjun; Zhao, Weizhong; Yuan, Xueling; He, Tingting; Jiang, Xingpeng] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China.
[Shi, Chuan] Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing, Peoples R China.
[Hu, Xiaohua] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.
通讯机构:
[Weizhong Zhao] H
Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University , Wuhan, Hubei 430079, P R China<&wdkj&>School of Computer Science, Beijing University of Posts and Telecommunications , Beijing, 100876, P R China<&wdkj&>National Language Resources Monitoring & Research Center for Network Media, Central China Normal University , Wuhan, Hubei 430079, P R China
语种:
英文
关键词:
drug–drug interaction;heterogeneous information network;meta-path-based information fusion
期刊:
BRIEFINGS IN BIOINFORMATICS
ISSN:
1467-5463
年:
2023
卷:
24
期:
2
基金类别:
National Natural Science Foundation of China [61872157, 61932008]; Fundamental Research Funds for Central Universities [KJ02502022-0450]; Scientific Research Center Program of National Language Commission [ZDI135-135]
机构署名:
本校为第一机构
院系归属:
计算机学院
摘要:
AbstractDrug–drug interactions (DDIs) are compound effects when patients take two or more drugs at the same time, which may weaken the efficacy of drugs or cause unexpected side effects. Thus, accurately predicting DDIs is of great significance for the drug development and the drug safety surveillance. Although many methods have been proposed for the task, the biological knowledge related to DDIs is not fully utilized and the complex semantics among drug-related biological entities are not effectively captured in existing methods, leading to s...

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