首页> 外文会议>Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on >Pathway analysis in the context of Bayesian networks - mathematical modeling of master and canalizing genes
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Pathway analysis in the context of Bayesian networks - mathematical modeling of master and canalizing genes

机译:贝叶斯网络背景下的途径分析-主基因和渠化基因的数学建模

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We utilize a tree-structured Bayesian network to characterize and detect master and canalizing genes via the coefficient of determination (CoD). Master genes possess strong regulation over groups of genes, whereas canalizing genes take over the regulation of large cohorts under certain cell conditions. While related, the two concepts are not the same and the analytic measures we employ reveal that difference. We also consider hypothesis testing for successful drug intervention in the framework of the Bayesian model.
机译:我们利用树结构的贝叶斯网络通过特征系数(CoD)表征和检测主控基因和渠化基因。掌握基因对基因组具有很强的调节作用,而在某些细胞条件下,渠化基因接管了大批研究对象的调节作用。虽然相关,但这两个概念并不相同,我们采用的分析方法揭示了这一差异。我们还考虑了在贝叶斯模型框架内成功进行药物干预的假设检验。

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