Screening drug-target interactions with positive-unlabeled learning
نویسندگان
چکیده
منابع مشابه
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning
Computational Drug Discovery, which uses computational techniques to facilitate and improve the drug discovery process, has aroused considerable interests in recent years. Drug Repositioning (DR) and DrugDrug Interaction (DDI) prediction are two key problems in drug discovery and many computational techniques have been proposed for them in the last decade. Although these two problems have mostl...
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Yixing Xu†, Chang Xu‡, Chao Xu†, Dacheng Tao‡ †Key Laboratory of Machine Perception (MOE), Cooperative Medianet Innovation Center, School of Electronics Engineering and Computer Science, PKU, Beijing 100871, China ‡UBTech Sydney AI Institute, The School of Information Technologies, The University of Sydney, J12, 1 Cleveland St, Darlington, NSW 2008, Australia [email protected], [email protected]...
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Drug-target interaction (DTI) prediction plays a very important role in drug development. Biochemical experiments or in vitro methods to identify such interactions are very expensive, laborious and time-consuming. Therefore, in silico approaches including docking simulation and machine learning have been proposed to solve this problem. In particular, machine learning approaches have attracted i...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2017
ISSN: 2045-2322
DOI: 10.1038/s41598-017-08079-7