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GEO(Gene Expression Omnibus ):高通量基因表达数据库
引用本文:刘华,马文丽,郑文岭.GEO(Gene Expression Omnibus ):高通量基因表达数据库[J].中国生物化学与分子生物学报,2007,23(3):236-244.
作者姓名:刘华  马文丽  郑文岭
作者单位:南方医科大学基因工程研究所,广州,510515
基金项目:广东省重点实验室启动基金
摘    要: GEO(Gene Expression Omnibus)数据库包括高通量实验数据的广泛分类,有单通道和双通道以微阵列为基础的对mRNA丰度的测定;基因组DNA和蛋白质分子的实验数据;其中包括来自以非阵列为基础的高通量功能基因组学和蛋白质组学技术的数据也被存档,例如基因表达系列分析(serial analysis of gene expression,SAGE)和蛋白质鉴定技术.迄今为止,GEO数据库包含的数据含概10 000个杂交实验和来自30种不同生物体的SAGE库.本文概述了GEO数据库的查询和浏览,数据下载和格式,数据分析,贮存与更新,并着重分析GEO数据浏览器中控制词汇的使用,阐述了GEO数据库的数据挖掘以及GEO在分子生物学领域中的应用前景.GEO可由此公众网址直接登陆http://www.ncbi.nlm.nih.gov/projects/geo/.

关 键 词:基因表达  数据库  控制词汇  数据挖掘
收稿时间:2006-9-26
修稿时间:2006年9月26日

GEO (Gene Expression Omnibus): High-throughput Gene Expression Database
LIU Hua,MA Wen-Li,ZHENG Wen-Ling.GEO (Gene Expression Omnibus): High-throughput Gene Expression Database[J].Chinese Journal of Biochemistry and Molecular Biology,2007,23(3):236-244.
Authors:LIU Hua  MA Wen-Li  ZHENG Wen-Ling
Institution:(Institute of Genetic Engineering,Southern Medical University,Guangzhou510515,China)
Abstract:The Gene Expression Omnibus (GEO) database, the first public repository for gene expression data, premiered at National Center for Biotechnology Information(NCBI) in July 2000. The GEO database contains a wide assortment of high-throughput experimental data, including single and dual channel microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules. Data are also archived which origin from non-array-based high-throughput functional genomics and proteomics technologies, including serial analysis of gene expression (SAGE) and protein identification technology. To date, the GEO database contains data representing almost 10 000 hybridization experiments and SAGE libraries from 30 different organisms. This paper outlines the query and browse in GEO database, data download, format, data analysis, and deposit and update. Also, it focuses on the managing terminology used in the GEO-data browser, while describing the course of data mining and GEO's future applications in the field of molecular biology. GEO is publicly accessible at http: www.ncbi.nlm.nih.gov/projects/geo/.
Keywords:gene expression  database  managing terminology  data mining
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