Holter N S, Mitra M, Maritan A, Cieplak M, Banavar J R, Fedoroff N V
Department of Physics and Center for Materials Physics, 104 Davey Laboratory, Consortium, 519 Wartik Laboratory, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Proc Natl Acad Sci U S A. 2000 Jul 18;97(15):8409-14. doi: 10.1073/pnas.150242097.
Analysis of previously published sets of DNA microarray gene expression data by singular value decomposition has uncovered underlying patterns or "characteristic modes" in their temporal profiles. These patterns contribute unequally to the structure of the expression profiles. Moreover, the essential features of a given set of expression profiles are captured using just a small number of characteristic modes. This leads to the striking conclusion that the transcriptional response of a genome is orchestrated in a few fundamental patterns of gene expression change. These patterns are both simple and robust, dominating the alterations in expression of genes throughout the genome. Moreover, the characteristic modes of gene expression change in response to environmental perturbations are similar in such distant organisms as yeast and human cells. This analysis reveals simple regularities in the seemingly complex transcriptional transitions of diverse cells to new states, and these provide insights into the operation of the underlying genetic networks.
通过奇异值分解对先前发表的DNA微阵列基因表达数据集进行分析，揭示了其时间分布中的潜在模式或“特征模式”。这些模式对表达谱结构的贡献并不均等。此外，仅使用少数特征模式就能捕捉到给定表达谱集的基本特征。这得出了一个惊人的结论，即基因组的转录反应是按照基因表达变化的一些基本模式精心编排的。这些模式既简单又稳健，主导着整个基因组中基因表达的变化。此外，在酵母和人类细胞等如此遥远的生物体中，基因表达响应环境扰动而变化的特征模式是相似的。该分析揭示了不同细胞向新状态看似复杂的转录转变中的简单规律，这些规律为潜在遗传网络的运作提供了见解。
