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题名: Ranking Candidate Disease Genes from Gene Expression and Protein Interaction: A Katz-Centrality Based Approach
作者: Zhao, J ;  Yang, TH ;  Huang, YX ;  Holme, P
刊名: PLOS ONE
出版日期: 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
学科分类: Physics
通讯作者: Zhao, J (reprint author), Logist Engn Univ, Dept Math, Chongqing, Peoples R China.
部门归属: [Zhao, Jing; Yang, Ting-Hong] Logist Engn Univ, Dept Math, Chongqing, Peoples R China; [Huang, Yongxu] Univ Pittsburgh, Dept Hlth Policy & Management, Pittsburgh, PA USA; [Holme, Petter] Umea Univ, Dept Phys, IceLab, Umea, Sweden; [Holme, Petter] Sungkyunkwan Univ, Dept Energy Sci, Suwon, South Korea; [Holme, Petter] Chinese Acad Sci, Kavli Inst Theoret Phys China, Beijing, 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.
资助者: National Natural Science Foundation of China [10971227]; Swedish Research Council; National Research Foundation of Korea; Ministry of Education, Science and Technology [R31-2008-10029]
收录类别: SCI
原文出处: 查看原文
语种: 英语
WOS记录号: WOS:000294686100033
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/14276
Appears in Collections:理论物理所2011年知识产出_期刊论文

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Recommended Citation:
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.
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