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A comparison between gene set and individual gene analyses using JProGO

机译:使用JPRogo基因集和单个基因分析的比较

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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:在上个世纪末开发的微阵列是生物技术历史中最重要的成就之一。微阵列最重要的应用是揭示表征不同样品或生物态的签名基因。该应用最初用于个体基因分析,但最近已被应用于基因集分析。我们比较这两种方法并使用JProgo(Java工具使用基因本体的原核微阵列数据的功能分析的Java工具进行比较。 JPRogo能够检查来自20多种不同的原核样品的微阵列数据,从而实现了对基因本体(GO)的基因行为数据的实际分析。两个大肠杆菌数据集用于比较两种分析的性能。结果表明,基因集分析更强大,因为它根据生物期望检测到GO条款的能力。该研究将为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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