期刊
DRUG DEVELOPMENT RESEARCH
卷 72, 期 2, 页码 219-224出版社
WILEY-BLACKWELL
DOI: 10.1002/ddr.20418
关键词
chemical space; genomic space; semi-supervised method; FLapRLS; drug-target interaction
资金
- National Natural Science Foundation of China [30900840]
- Fundamental Research Funds for the Central Universities
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. (C) 2010 Wiley-Liss, Inc.
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