Zhang Bing, Schmoyer Denise, Kirov Stefan, Snoddy Jay
Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
BMC Bioinformatics. 2004 Feb 18;5:16. doi: 10.1186/1471-2105-5-16.
Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.
We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at http://genereg.ornl.gov/gotm/.
GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets.
微阵列及其他高通量技术正在产生大量难以直接分析的有趣基因集。需要生物信息学工具来解读基因集中的功能信息。
我们创建了一个基于网络的工具,用于对基因集进行数据分析和数据可视化,称为基因本体树机器(GOTM)。该工具最初旨在分析从微阵列分析中鉴定出的共调控基因集,但也适用于来自其他高通量分析的其他基因集。基因本体树机器生成一个基因本体树,这是一种树状结构,用于在输入基因集的基因本体有向无环图中导航。该系统提供用户友好的数据导航和可视化。统计分析帮助用户识别输入基因集最重要的基因本体类别,并建议值得进一步研究的生物学领域。基因本体树机器可在http://genereg.ornl.gov/gotm/在线获取。
基因本体树机器在功能基因组学、蛋白质组学及其他产生大量有趣基因集的高通量方法中具有广泛应用;其主要目的是帮助用户在基因集中筛选出有趣的模式。