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A probabilistic functional network of yeast genes

机译:酵母基因的概率功能网络

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A conceptual framework for integrating diverse functional genomics data was developed by reinterpreting experiments to provide numerical likelihoods that genes are functionally linked. This allows direct comparison and integration of different classes of data. The resulting probabilistic gene network estimates the functional coupling between genes. Within this framework, we reconstructed an extensive, high-quality functional gene network for Saccharomyces cerevisiae, consisting of 4681 (similar to81%) of the known yeast genes linked by similar to34,000 probabilistic linkages comparable in accuracy to small-scale interaction assays. The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis.
机译:通过重新解释实验来开发一种整合各种功能基因组学数据的概念框架,以提供基因功能性关联的数值可能性。这样可以直接比较和集成不同类别的数据。由此产生的概率基因网络估计了基因之间的功能耦合。在此框架内,我们为酿酒酵母构建了一个广泛的,高质量的功能基因网络,该网络由4681个(约占81%)已知酵母基因组成,这些酵母基因通过与34,000个概率连锁相似的精度可与小规模相互作用分析相媲美。集成的链接将早期数据集中的真假互动与真假互动区分开来。如基因在染色质修饰和核糖体生物发生中所示,新的相互作用从基因的网络环境中出现。

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