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A comparison between gene set and individual gene analyses using JProGO

机译:使用JProGO对基因集和单个基因进行分析的比较

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Microarray, developed at the end of the last century, is one of the most significant achievements in biotechnology history. One of the most important applications of microarrays is to uncover the signature genes characterizing different samples or biological states. This application was initially used in individual gene analysis, but recently has been applied to gene set analysis. We compare these two approaches and compare the performance using JProGO (Java Tool for the Functional Analysis of Prokaryotic Microarray Data using the Gene Ontology). JProGO is able to examine microarray data from more than 20 different samples of prokaryotic and thus practical analysis of gene behavior data with regards to Gene Ontology (GO) is made possible. Two Escherichia coli datasets are used to compare the performance of the two analyses. The results show that the gene set analysis is more powerful because of its ability to detect the GO terms according to biological expectation. This research will provide a new platform and opportunities for further research or studies in microarray based gene sets.
机译:上个世纪末开发的微阵列是生物技术历史上最重要的成就之一。微阵列最重要的应用之一是揭示表征不同样品或生物学状态的特征基因。此应用程序最初用于单个基因分析,但最近已应用于基因集分析。我们比较了这两种方法,并比较了使用JProGO(使用基因本体对原核微阵列数据进行功能分析的Java工具)的性能。 JProGO能够检查来自20多个不同原核样品的微阵列数据,因此可以进行有关基因本体论(GO)的基因行为数据的实际分析。使用两个大肠杆菌数据集来比较两个分析的性能。结果表明,基因集分析功能强大,因为它能够根据生物学期望检测GO项。这项研究将为基于微阵列基因集的进一步研究或研究提供新的平台和机会。

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