ArticleBMC bioinformatics2006
Computational reconstruction of transcriptional regulatory modules of the yeast cell cycle.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Application of Transcriptional Gene Modules to Analysis ofG3 (Bethesda, Md.) · 2020Article
- YGMD: a repository for yeast cooperative transcription factor sets and their target gene modules.Database : the journal of biological databases and curation · 2017Article
- Article
- YCRD: Yeast Combinatorial Regulation Database.PloS one · 2016Article
- CoopTFD: a repository for predicted yeast cooperative transcription factor pairs.Database : the journal of biological databases and curation · 2016Article
- Functional redundancy of transcription factors explains why most binding targets of a transcription factor are not affected when the transcription factor is knocked out.BMC systems biology · 2015Article
- Periodic mRNA synthesis and degradation co-operate during cell cycle gene expression.Molecular systems biology · 2014Article
- Systematic identification of transcriptional regulatory modules from protein-protein interaction networks.Nucleic acids research · 2014Article
- Article
- Missing value imputation for microarray data: a comprehensive comparison study and a web tool.BMC systems biology · 2013Article
- Shrinkage regression-based methods for microarray missing value imputation.BMC systems biology · 2013Article
- Evolution of transcriptional regulation in closely related bacteria.BMC evolutionary biology · 2012Article
- Identifying biologically interpretable transcription factor knockout targets by jointly analyzing the transcription factor knockout microarray and the ChIP-chip data.BMC systems biology · 2012Article
- Constructing gene regulatory networks for long term photosynthetic light acclimation in Arabidopsis thaliana.BMC bioinformatics · 2011Article
- Uncovering the transcriptional circuitry in skeletal muscle regeneration.Mammalian genome : official journal of the International Mammalian Genome Society · 2011Article
- Different Functional Gene Clusters in Yeast have Different Spatial Distributions of the Transcription Factor Binding Sites.Bioinformatics and biology insights · 2011Article
- TF-centered downstream gene set enrichment analysis: Inference of causal regulators by integrating TF-DNA interactions and protein post-translational modifications information.BMC bioinformatics · 2010Article
- Identifying a Transcription Factor's Regulatory Targets from its Binding Targets.Gene regulation and systems biology · 2010Article
- The transcriptional network activated by Cln3 cyclin at the G1-to-S transition of the yeast cell cycle.Genome biology · 2010Article
- Transcriptional programs: modelling higher order structure in transcriptional control.BMC bioinformatics · 2009Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundA transcriptional regulatory module (TRM) is a set of genes that is regulated by a common set of transcription factors (TFs). By organizing the genome into TRMs, a living cell can coordinate the activities of many genes and carry out complex functions. Therefore, identifying TRMs is helpful for understanding gene regulation.
resultsIntegrating gene expression and ChIP-chip data, we develop a method, called MOdule Finding Algorithm (MOFA), for reconstructing TRMs of the yeast cell cycle. MOFA identified 87 TRMs, which together contain 336 distinct genes regulated by 40 TFs. Using various kinds of data, we validated the biological relevance of the identified TRMs. Our analysis shows that different combinations of a fairly small number of TFs are responsible for regulating a large number of genes involved in different cell cycle phases and that there may exist crosstalk between the cell cycle and other cellular processes. MOFA is capable of finding many novel TF-target gene relationships and can determine whether a TF is an activator or/and a repressor. Finally, MOFA refines some clusters proposed by previous studies and provides a better understanding of how the complex expression program of the cell cycle is regulated.
conclusionMOFA was developed to reconstruct TRMs of the yeast cell cycle. Many of these TRMs are in agreement with previous studies. Further, MOFA inferred many interesting modules and novel TF combinations. We believe that computational analysis of multiple types of data will be a powerful approach to studying complex biological systems when more and more genomic resources such as genome-wide protein activity data and protein-protein interaction data become available.
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