Revealing modular organization in the yeast transcriptional network
Revealing modular organization in the yeast transcriptional network
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DOI：
10.1038/ng941
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发表时间：
2002-08-01
期刊：
影响因子：
30.8
通讯作者：
Barkai, N
中科院分区：
文献类型：
--
作者：
Ihmels, J;Friedlander, G;Barkai, N
标准聚类方法在应用于相对小的数据集时可以成功地对基因进行分类，但在大规模表达数据的分析中使用有限，主要是由于它们将基因分配给单个聚类。在这里，我们提出了一种替代方法，用于全基因组表达数据的全局分析。我们的方法分配基因的上下文相关的和潜在的重叠的“转录模块”，从而克服了传统的聚类方法的主要局限性。我们用我们的方法来阐明细胞通路的调控特性，并表征顺式调控元件。通过将我们的算法系统地应用于所有可用的酿酒酵母表达数据，我们确定了一套全面的重叠转录模块。我们的研究结果提供了许多基因的功能预测，确定模块之间的关系，并提出了一个全球性的看法的转录网络。
Standard clustering methods can classify genes successfully when applied to relatively small data sets, but have limited use in the analysis of large-scale expression data, mainly owing to their assignment of a gene to a single cluster. Here we propose an alternative method for the global analysis of genome-wide expression data. Our approach assigns genes to context-dependent and potentially overlapping 'transcription modules', thus overcoming the main limitations of traditional clustering methods. We use our method to elucidate regulatory properties of cellular pathways and to characterize cis-regulatory elements. By applying our algorithm systematically to all of the available expression data on Saccharomyces cerevisiae, we identify a comprehensive set of overlapping transcriptional modules. Our results provide functional predictions for numerous genes, identify relations between modules and present a global view on the transcriptional network.