Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data
Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data
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DOI：
10.1038/ng1165
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发表时间：
2003-06-01
期刊：
影响因子：
30.8
通讯作者：
Friedman, N
中科院分区：
文献类型：
--
作者：
Segal, E;Shapira, M;Friedman, N
一个细胞的大部分活动都是由相互作用的模块组成的网络：一组基因共同调节以响应不同的条件。我们提出了一种概率方法，从基因表达数据中识别调控模块。我们的程序确定模块的共调节基因，它们的监管机构和条件下发生的调节，产生可检验的假设的形式调节X调节模块Y的条件下W '。我们将该方法应用于酿酒酵母表达数据集，显示其识别功能一致的模块及其正确调节器的能力。我们目前的微阵列实验支持三种新的预测，表明以前未知的蛋白质的调节作用。
Much of a cell's activity is organized as a network of interacting modules: sets of genes coregulated to respond to different conditions. We present a probabilistic method for identifying regulatory modules from gene expression data. Our procedure identifies modules of coregulated genes, their regulators and the conditions under which regulation occurs, generating testable hypotheses in the form regulator X regulates module Y under conditions W'. We applied the method to a Saccharomyces cerevisiae expression data set, showing its ability to identify functionally coherent modules and their correct regulators. We present microarray experiments supporting three novel predictions, suggesting regulatory roles for previously uncharacterized proteins.