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dc.contributor.authorWang, Hwei-Mingen_US
dc.contributor.authorChang, Tzu-Haoen_US
dc.contributor.authorLin, Feng-Maoen_US
dc.contributor.authorChao, Te-Hsinen_US
dc.contributor.authorHuang, Wei-Chihen_US
dc.contributor.authorLiang, Chaoen_US
dc.contributor.authorChu, Chao-Fangen_US
dc.contributor.authorChiu, Chih-Minen_US
dc.contributor.authorWu, Wei-Yunen_US
dc.contributor.authorChen, Ming-Chengen_US
dc.contributor.authorWeng, Chen-Tsungen_US
dc.contributor.authorWeng, Shun-Longen_US
dc.contributor.authorChiang, Feng-Fanen_US
dc.contributor.authorHuang, Hsien-Daen_US
dc.date.accessioned2014-12-08T15:29:42Z-
dc.date.available2014-12-08T15:29:42Z-
dc.date.issued2013-04-10en_US
dc.identifier.issn0378-1119en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.gene.2012.11.067en_US
dc.identifier.urihttp://hdl.handle.net/11536/21324-
dc.description.abstractRecently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development. (c) 2012 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectGenome-Wide Association Studiesen_US
dc.subjectGWASen_US
dc.subjectSingle-nucleotide polymorphismen_US
dc.subjectSNPen_US
dc.subjectColorectal canceren_US
dc.subjectRisk predictionen_US
dc.titleA new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwanen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.doi10.1016/j.gene.2012.11.067en_US
dc.identifier.journalGENEen_US
dc.citation.volume518en_US
dc.citation.issue1en_US
dc.citation.spage107en_US
dc.citation.epage113en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000316424100015-
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