Computational Study of Drugs by Integrating Omics Data with Kernel Methods

doi:10.1002/minf.201300090

NWIPB OpenIR

	Computational Study of Drugs by Integrating Omics Data with Kernel Methods
	Wang, Yongcui C.1; Deng, Naiyang 2; Chen, Shilong1 ; Wang, Yong 3,4; Wang, YCC (reprint author), Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, 23 Xinning Rd, Xining, Qinghai Provinc, Peoples R China.
	2013-12-01
发表期刊	MOLECULAR INFORMATICS
ISSN	1868-1743
卷号	32 期号:11-12 页码:930-941
文章类型	Review
摘要	With the rapid development of genomic and chemogenomic techniques, many omics data sources for drugs have been publicly available. These data sources illustrate drug's biological function in the living cell from different levels and different aspects. One straightforward idea is to learn understandable rules via computational models and algorithms to mine and integrate these data sources. Here, we review our recent efforts on developing kernel-based methods to integrate drug related omics data sources. Three promising applications of our framework are shown to predict drug targets, assign drug's ATC-code annotation, and reveal drug repositioning. We demonstrate that data integration does provide more information and improve the accuracy by recovering more experimentally observed target proteins, ATC-codes, and drug repositioning. Importantly, data integration can indicate novel predictions which are supported by database search and functional annotation analysis and worthy of further experimental validation. In conclusion, kernel methods can efficiently integrate heterogeneous data sources to computationally study drugs, and will promote the further research in drug discovery in a low-cost way.; With the rapid development of genomic and chemogenomic techniques, many omics data sources for drugs have been publicly available. These data sources illustrate drug's biological function in the living cell from different levels and different aspects. One straightforward idea is to learn understandable rules via computational models and algorithms to mine and integrate these data sources. Here, we review our recent efforts on developing kernel-based methods to integrate drug related omics data sources. Three promising applications of our framework are shown to predict drug targets, assign drug's ATC-code annotation, and reveal drug repositioning. We demonstrate that data integration does provide more information and improve the accuracy by recovering more experimentally observed target proteins, ATC-codes, and drug repositioning. Importantly, data integration can indicate novel predictions which are supported by database search and functional annotation analysis and worthy of further experimental validation. In conclusion, kernel methods can efficiently integrate heterogeneous data sources to computationally study drugs, and will promote the further research in drug discovery in a low-cost way.
关键词	Omics Data Kernel Methods Data Integration Drug-targets Atc-codes Of Drugs Drug Repositioning
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
DOI	10.1002/minf.201300090
关键词[WOS]	PROTEIN INTERACTION PREDICTION ; TARGET RELATIONSHIPS ; SEQUENCE ; IDENTIFICATION ; KNOWLEDGEBASE ; SIMILARITY ; MACHINE ; GENES
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(11201470 ; 31270270 ; 11131009 ; 61171007 ; 11371365 ; 11071252)
WOS研究方向	Pharmacology & Pharmacy ; Mathematical & Computational Biology
WOS类目	Chemistry, Medicinal ; Mathematical & Computational Biology
WOS记录号	WOS:000330109500006
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/3890
专题	中国科学院西北高原生物研究所
通讯作者	Wang, YCC (reprint author), Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, 23 Xinning Rd, Xining, Qinghai Provinc, Peoples R China.
作者单位	1.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining, Qinghai Provinc, Peoples R China 2.China Agr Univ, Coll Sci, Beijing 100094, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China 4.Natl Inst Adv Ind Sci & Technol, Mol Profiling Res Ctr Drug Discovery, Tokyo, Japan
推荐引用方式 GB/T 7714	Wang, Yongcui C.,Deng, Naiyang,Chen, Shilong,et al. Computational Study of Drugs by Integrating Omics Data with Kernel Methods[J]. MOLECULAR INFORMATICS,2013,32(11-12):930-941.
APA	Wang, Yongcui C.,Deng, Naiyang,Chen, Shilong,Wang, Yong,&Wang, YCC .(2013).Computational Study of Drugs by Integrating Omics Data with Kernel Methods.MOLECULAR INFORMATICS,32(11-12),930-941.
MLA	Wang, Yongcui C.,et al."Computational Study of Drugs by Integrating Omics Data with Kernel Methods".MOLECULAR INFORMATICS 32.11-12(2013):930-941.

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