Title
Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data.
Abstract
ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. However, the binding of a TF to a gene does not necessarily imply regulation. Thus, it is important to develop methods to identify regulatory targets of TFs from ChIP-chip data.We developed a method, called Temporal Relationship Identification Algorithm (TRIA), which uses gene expression data to identify a TF's regulatory targets among its binding targets inferred from ChIP-chip data. We applied TRIA to yeast cell cycle microarray data and identified many plausible regulatory targets of cell cycle TFs. We validated our predictions by checking the enrichments for functional annotation and known cell cycle genes. Moreover, we showed that TRIA performs better than two published methods (MA-Network and MFA). It is known that co-regulated genes may not be co-expressed. TRIA has the ability to identify subsets of highly co-expressed genes among the regulatory targets of a TF. Different functional roles are found for different subsets, indicating the diverse functions a TF could have. Finally, for a control, we showed that TRIA also performs well for cell-cycle irrelevant TFs.Finding the regulatory targets of TFs is important for understanding how cells change their transcription program to adapt to environmental stimuli. Our algorithm TRIA is helpful for achieving this purpose.
Year
DOI
Venue
2007
10.1186/1471-2105-8-188
BMC Bioinformatics
Keywords
Field
DocType
gene expression profiling,transcription factor,cell cycle,gene expression,algorithms,microarray data,microarrays,transcription factors,chip,bioinformatics
Cell Cycle Gene,Gene,Biology,Gene expression,Cell cycle,Bioinformatics,Genetics,Cell Cycle Protein,Transcription factor,DNA microarray,Gene expression profiling
Journal
Volume
Issue
ISSN
8
1
1471-2105
Citations 
PageRank 
References 
25
0.80
11
Authors
3
Name
Order
Citations
PageRank
Wei-Sheng Wu114112.08
Wen-Hsiung Li233624.03
Bor-Sen Chen32640228.84