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High-Throughput GoMiner an industrial-strength integrative gene ontology tool for interpretation of multiple-microarray experiments with application to studies of Common Variable Immune Deficiency (CVID)

机译:高通量GoMiner一种工业强度整合基因本体论工具用于解释多微阵列实验并应用于常见可变免疫缺乏症(CVID)的研究

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摘要

BackgroundWe previously developed GoMiner, an application that organizes lists of 'interesting' genes (for example, under-and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. The original version of GoMiner was oriented toward visualization and interpretation of the results from a single microarray (or other high-throughput experimental platform), using a graphical user interface. Although that version can be used to examine the results from a number of microarrays one at a time, that is a rather tedious task, and original GoMiner includes no apparatus for obtaining a global picture of results from an experiment that consists of multiple microarrays. We wanted to provide a computational resource that automates the analysis of multiple microarrays and then integrates the results across all of them in useful exportable output files and visualizations.
机译:背景我们之前开发了GoMiner,该应用程序可以组织``有趣的''基因列表(例如,来自微阵列实验的表达不足和过表达的基因),以便在基因本体论的背景下进行生物学解释。 GoMiner的原始版本旨在使用图形用户界面对单个微阵列(或其他高通量实验平台)的结果进行可视化和解释。尽管可以使用该版本一次检查多个微阵列的结果,但这是一项繁琐的工作,原始的GoMiner不包含用于从由多个微阵列组成的实验中获得全局结果的设备。我们希望提供一种计算资源,该资源可以自动分析多个微阵列,然后将所有微阵列的结果集成到有用的可导出输出文件和可视化文件中。

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