title: A survey on the computational approaches to identify drug targets in the postgenomic era.
abstract: Identifying drug targets plays essential roles in designing new drugs and combating diseases. Unfortunately, our current knowledge about drug targets is far from comprehensive. Screening drug targets in the lab is an expensive and time-consuming procedure. In the past decade, the accumulation of various types of omics data makes it possible to develop computational approaches to predict drug targets. In this paper, we make a survey on the recent progress being made on computational methodologies that have been developed to predict drug targets based on different kinds of omics data and drug property data.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai 200444, China ; Department of Mathematics, Shanghai University, Shanghai 200444, China.
authors.forename: Yan-Fen
authors.initials: YF
authors.lastname: Dai
authors.affiliation: Department of Computer Science, School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ; Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Xing-Ming
authors.identifier: 0000-0002-3335-6439
authors.initials: XM
authors.lastname: Zhao
mesh_terms: D019295:Computational Biology / Q000379:methods / Q000639:trends; D062313:Databases, Pharmaceutical; D016503:Drug Delivery Systems; D015195:Drug Design; D020869:Gene Expression Profiling; D023281:Genomics; D006801:Humans; D060066:Protein Interaction Maps; D011795:Surveys and Questionnaires