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BayGO: Bayesian analysis of ontology term enrichment in microarray data

机译:BayGO:微阵列数据中本体术语丰富化的贝叶斯分析

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摘要

BackgroundThe search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem.
机译:背景技术在从微阵列实验获得的基因列表中寻找丰富的(又名过度代表或增强的)本体术语正在成为系统级分析的标准程序。此过程试图总结集中在分类设计(例如基因本体论,KEGG途径等)上的信息,而不是集中在单个基因上。尽管在统计中众所周知关联和重要性是截然不同的概念,但是仅使用前一种方法来处理本体术语丰富问题。

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