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标题:Predicting drug-target interactions based on an improved semi-supervised learning approach
时间:2020-02-14 17:40:27
DOI:10.1002/ddr.20418
作者:Weiming Yu; Xuan Cheng; Zhibin Li
关键词:chemical space;genomic space;semi-supervised method;FLapRLS;drug-target interaction;
出版源: 《Drug Development Research》 ,72 (2) :219-224
摘要:Abstract Identifying interactions between compounds and target proteins is an important area of research in drug discovery and there is thus a strong incentive to develop computational approaches capable of detecting these potential compound-protein interactions efficiently. In this study, two different methods were first utilized to construct chemical and genomic spaces, respectively. Then two spaces were combined into a integrate space to discover the potential compound-target pairs in the known drug-target interaction data by an improved semi-supervised learning method (FLapRLS). The results demonstrated that this prediction method is effective. Drug Dev Res 72: 219–224, 2011.  © 2010 Wiley-Liss, Inc.
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