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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >COMPUTATIONAL GENE KNOCKOUT REVEALS TRANSDISEASE–TRANSGENE ASSOCIATION STRUCTURE
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COMPUTATIONAL GENE KNOCKOUT REVEALS TRANSDISEASE–TRANSGENE ASSOCIATION STRUCTURE

机译：计算基因敲除揭示了转基因-转基因的关联结构

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摘要

Genome-wide association studies for a variety of diseases are identifying increasing numbers of candidate genes. Now we are confronted with the fact that some genes are common candidates across diseases. Thus there is a strong need to develop a hypothesis formulation methodology to comprehend multifaceted associations between genes and diseases. We have developed a computational method for building transdisease–transgene association structure. By introducing the basic rationale underlying the gene knockout approach as an information processing procedure to a network constructed on the basis of hyperlinks between disease and gene pages listed in the Online Mendelian Inheritance in Man (OMIM) database, relations of genes with diseases are computationally quantified. We did successively eliminate gene pages (called "computational gene knockout" in this paper) expected to contribute to metabolic syndrome, and catalogued each association with various disease pages. We thereby apply a co-clustering method to the gene–disease relations to obtain an association structure by classifying diseases and genes simultaneously. Observing an association structure between over 100 diseases and their related genes, we then found that the structure revealed gene classes that were commonly associated with diseases as well as gene classes that were selectively associated with a specific disease class.
机译：对各种疾病的全基因组关联研究正在确定越来越多的候选基因。现在，我们面对一个事实，即某些基因是跨疾病的常见候选者。因此，迫切需要开发一种假设表述方法来理解基因与疾病之间的多方面关联。我们已经开发出一种计算方法来构建转染-转基因关联结构。通过将基因敲除法的基本原理作为信息处理程序引入网络，该网络是基于疾病和人在线孟德尔遗传（OMIM）数据库中列出的基因页面之间的超链接构建的网络，可通过计算量化基因与疾病的关系。我们确实消除了预期会导致代谢综合征的基因页面（在本文中称为“计算基因敲除”），并列出了与各种疾病页面的每个关联。因此，我们将共聚方法应用于基因-疾病关系，以便通过同时对疾病和基因进行分类来获得关联结构。通过观察100多种疾病及其相关基因之间的关联结构，我们发现该结构揭示了通常与疾病相关的基因类别以及与特定疾病类别选择性相关的基因类别。

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    TSUTOMU MATSUNAGA; SHUHEI KUWATA; MASAAKI MURAMATSU;

  • 作者单位

    TSUTOMU MATSUNAGA Research and Development Headquarters, NTT Data Corporation, 3-3-9 Toyosu, Koto-ku, Tokyo 135-8671, Japanmatsunagat@nttdata.co.jp SHUHEI KUWATA Research and Development Headquarters, NTT Data Corporation, 3-3-9 Toyosu, Koto-ku, Tokyo 135-8671, Japankuwatas@nttdata.co.jp MASAAKI MURAMATSU Medical Research Institute, Tokyo Medical and Dental University, 2-3-10 Kanda-surugadai, Chiyoda-ku, Tokyo 101-0062, JapanResearch Institute, HuBit Genomix Inc., 7-10-2 Tsukiji, Chuo-ku, Tokyo 104-0045, Japanmuramatsu.epi@mri.tmd.ac.jp;

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  • 正文语种 eng
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  • 关键词

    Data mining; gene relation network; nosology; metabolic syndrome.;

    机译：数据挖掘;基因关系网络;疾病学代谢综合征。;

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