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鉴定酵母细胞周期转录因子的统计方法。

Statistical methods for identifying yeast cell cycle transcription factors.

作者信息

Tsai Huai-Kuang, Lu Henry Horng-Shing, Li Wen-Hsiung

机构信息

Genomics Research Center, Academia Sinica, Nankang, Taipei 115, Taiwan.

出版信息

Proc Natl Acad Sci U S A. 2005 Sep 20;102(38):13532-7. doi: 10.1073/pnas.0505874102. Epub 2005 Sep 12.

Abstract

Knowing transcription factors (TFs) involved in the yeast cell cycle is helpful for understanding the regulation of yeast cell cycle genes. We therefore developed two methods for predicting (i) individual cell cycle TFs and (ii) synergistic TF pairs. The essential idea is that genes regulated by a cell cycle TF should have higher (lower, if it is a repressor) expression levels than genes not regulated by it during one or more phases of the cell cycle. This idea can also be used to identify synergistic interactions of TFs. Applying our methods to chromatin immunoprecipitation data and microarray data, we predict 50 cell cycle TFs and 80 synergistic TF pairs, including most known cell cycle TFs and synergistic TF pairs. Using these and published results, we describe the behaviors of 50 known or inferred cell cycle TFs in each cell cycle phase in terms of activation/repression and potential positive/negative interactions between TFs. In addition to the cell cycle, our methods are also applicable to other functions.

摘要

了解参与酵母细胞周期的转录因子(TFs)有助于理解酵母细胞周期基因的调控。因此,我们开发了两种方法来预测:(i)单个细胞周期转录因子;(ii)协同转录因子对。其基本思想是,在细胞周期的一个或多个阶段,受细胞周期转录因子调控的基因应比不受其调控的基因具有更高(如果是阻遏物则更低)的表达水平。这个想法也可用于识别转录因子的协同相互作用。将我们的方法应用于染色质免疫沉淀数据和微阵列数据,我们预测了50个细胞周期转录因子和80对协同转录因子对,包括大多数已知的细胞周期转录因子和协同转录因子对。利用这些以及已发表的结果,我们从激活/抑制以及转录因子之间潜在的正/负相互作用方面描述了50个已知或推断的细胞周期转录因子在每个细胞周期阶段的行为。除了细胞周期,我们的方法也适用于其他功能。

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