Drug-target interaction prediction: databases, web servers and computational models

doi:10.1093/bib/bbv066

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Drug-target interaction prediction: databases, web servers and computational models
	Chen, Xing 2; Yan, Chenggang Clarence 5; Zhang, Xiaotian 1; Zhang, Xu 1; Dai, Feng 3; Yin, Jian 4; Zhang, Yongdong 3
刊名	BRIEFINGS IN BIOINFORMATICS
	2016-07-01
卷号	17 期号:4 页码:696-712
关键词	drug-target interactions prediction drug discovery computational models biological networks machine learning
ISSN号	1467-5463
DOI	10.1093/bib/bbv066
英文摘要	Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.
资助项目	National Natural Science of Foundation of China[11301517] ; National Natural Science of Foundation of China[61472203] ; National Natural Science of Foundation of China[61327902] ; foundation from National Center for Mathematics and Interdisciplinary Sciences, CAS ; State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
语种	英语
出版者	OXFORD UNIV PRESS
WOS记录号	WOS:000383151200013
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/8164]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Xing
作者单位	1.Shandong Univ, Sch Mech Elect & Informat Engn, Jinan, Peoples R China 2.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Zhongguancun East Rd, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Shandong Univ, Dept Comp, Jinan, Peoples R China 5.Tsinghua Univ, Dept Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Chen, Xing,Yan, Chenggang Clarence,Zhang, Xiaotian,et al. Drug-target interaction prediction: databases, web servers and computational models[J]. BRIEFINGS IN BIOINFORMATICS,2016,17(4):696-712.
APA	Chen, Xing.,Yan, Chenggang Clarence.,Zhang, Xiaotian.,Zhang, Xu.,Dai, Feng.,...&Zhang, Yongdong.(2016).Drug-target interaction prediction: databases, web servers and computational models.BRIEFINGS IN BIOINFORMATICS,17(4),696-712.
MLA	Chen, Xing,et al."Drug-target interaction prediction: databases, web servers and computational models".BRIEFINGS IN BIOINFORMATICS 17.4(2016):696-712.