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National Chung Hsing University Institutional Repository - NCHUIR > 生命科學院 > 基因體暨生物資訊學研究所 > 依資料類型分類 > 期刊論文 >  Bayesian approach to transforming public gene expression repositories into disease diagnosis databases

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/133546

標題: Bayesian approach to transforming public gene expression repositories into disease diagnosis databases
作者: Huang, H.Y.;Liu, C.C.;Zhou, X.J.
劉俊吉
關鍵字: microarray data;classification;omnibus;search;cancer
日期: 2010
Issue Date: 2012-12-14 10:01:08 (UTC+8)
關連: Proceedings of the National Academy of Sciences of the United States of America, Volume 107, Issue 15, Page(s) 6823-6828.
摘要: The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also demonstrated that the power of our method can increase significantly with the continued growth of public gene expression repositories. Finally, we showed how our disease diagnosis system can be used to characterize complex phenotypes and to construct a disease-drug connectivity map.
Relation: Proceedings of the National Academy of Sciences of the United States of America
Appears in Collections:[依資料類型分類] 期刊論文
[依教師分類] 劉俊吉
[依教師分類] 劉俊吉

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