Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach

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	Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach
	Zhao, J ; Yang, TH ; Huang, YX ; Holme, P
刊名	PLOS ONE
	2011
卷号	6 期号:9 页码:e24306
关键词	GENOME-WIDE ASSOCIATION ONSET ALZHEIMER-DISEASE MICROARRAY DATA INTERACTION NETWORKS IDENTIFICATION PRIORITIZATION POLYMORPHISM PATHOLOGY MODEL RISK
ISSN号	1932-6203
通讯作者	Zhao, J (reprint author), Logist Engn Univ, Dept Math, Chongqing, Peoples R China.
英文摘要	Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions-that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.
学科主题	Physics
收录类别	SCI
资助信息	National Natural Science Foundation of China [10971227]; Swedish Research Council; National Research Foundation of Korea; Ministry of Education, Science and Technology [R31-2008-10029]
原文出处	http://dx.doi.org/10.1371/journal.pone.0024306
语种	英语
WOS记录号	WOS:000294686100033
公开日期	2013-05-17
内容类型	期刊论文
源URL	[http://ir.itp.ac.cn/handle/311006/14276]
专题	理论物理研究所_理论物理所1978-2010年知识产出
推荐引用方式 GB/T 7714	Zhao, J,Yang, TH,Huang, YX,et al. Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach[J]. PLOS ONE,2011,6(9):e24306.
APA	Zhao, J,Yang, TH,Huang, YX,&Holme, P.(2011).Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach.PLOS ONE,6(9),e24306.
MLA	Zhao, J,et al."Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach".PLOS ONE 6.9(2011):e24306.