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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51283

Title: Statistical methods for identifying yeast cell cycle transcription factors
Authors: Tsai HK
Lu HH
Li WH
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: cell cycle regulators
microarray data
synergistic interactions
Date: 2005-09
Issue Date: 2018-11-21T07:50:22Z
Publisher: Proc Natl Acad Sci
Abstract: 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.
Relation: 102(38) pp.13532-13537
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51283
Appears in Collections:[資訊工程學系] 期刊論文

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