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Genome-level integration of gene functional information and its application to elucidation of gene systems

基因功能信息的基因组水平整合及其在阐明基因系统中的应用

基本信息

批准号：
15011229
负责人：
MATSUDA Hideo
金额：
$ 20.48万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research on Priority Areas
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

项目摘要

Although a large amount of data about genes from the genomes of many organisms has been obtained, the filmdom of many genes are still uncharacterized. This was due to the facts that the information of gene functions were not systematically arranged and not easily utilized, and the method for classifying genes to the gene families of functionally-coupled groups with their sequence homologies or expression similarities. To cope with these issues, this study aims to elucidate gene systems focusing on gene interactions by developing methods for systematic extraction of clearly-characterized gene functions and systematic arrangement of the extracted functional information in genome level.The achievements of this study are:(1) More accurate inference of gene regulatory networks with Bayesian network from gene expression data by using the functional classification of Gene Ontology as well as expression similarity.(2) Mapping genes on microarrays onto the KEGG metabolic pathway database, construction of the system for analyzing the genes with their microarray data, the computational analysis of the tryptophan degradation pathway in mouse and the prediction of the existence of an alternative pathway.(3) Development of analysis pipeline called SayaMatcher for finding the transcription-factor binding sites of which number is expected as several thousands to several hundreds of thousands.(4) Construction of a DAS (Distributed Annotation System) server that makes it possible to display and browse those found binding sites and their positions on the genome.

尽管人们已经从许多生物的基因组中获得了大量的基因数据，但许多基因的膜结构仍然是未知的。这是由于基因功能信息没有系统地整理和利用，以及根据基因序列同源性或表达相似性将基因分类到功能偶联组的基因家族的方法。科普这些问题，本研究旨在通过系统地提取具有明确特征的基因功能，并在基因组水平上对提取的功能信息进行系统的整理，来阐明以基因相互作用为重点的基因系统，取得了以下研究成果：（1）利用基因本体的功能分类和表达相似性，利用贝叶斯网络从基因表达数据中更准确地推断基因调控网络。(2)将微阵列上的基因定位到KEGG代谢途径数据库中，构建基因微阵列数据分析系统，计算分析小鼠色氨酸降解途径，预测替代途径的存在。(3)开发名为SayaMatcher的分析管道，用于寻找转录因子结合位点，其数量预计为数千至数十万。(4)构建DAS（分布式注释系统）服务器，该服务器可以显示和浏览那些发现的结合位点及其在基因组上的位置。