Abstract
A considerable fraction of yeast gene promoters are bound by multiple transcription factors. To study the combinatorial interactions of multiple transcription factors is thus important in understanding gene regulation. In this paper, we propose a computational method to identify the co-regulated gene groups and regulatory programs of multiple transcription factors from protein-DNA binding and gene expression data. The key concept is to characterize a regulatory program in terms of two properties of individual transcription factors: the function of a regulator as an activator or a repressor, and its direction of effectiveness as necessary or sufficient. We apply a greedy algorithm to find the regulatory models which optimally fit the data. Empirical analysis indicates the inferred regulatory models agree with the known combinatorial interactions between regulators and are robust against the settings of various free parameters.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
McNabb, D., et al.: Cloning of yeast HAP5: a novel subunit of a heterotrimeric complex required for CCAAT binding. Genes Development 9(1), 47–58 (1995)
Friedman, N., et al.: Using Bayesian networks to analyze expression data. Journal of Computational Biology 7, 601–620 (2000)
Hartemink, A., et al.: Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. Pacific Symposium of Biocomputing, 422–433 (2001)
Segal, E., et al.: From promoter sequence to expression: a probabilistic framework. In: Proceedings of the 6th International Conference on Research in Computational Molecular Biology, pp. 263–272 (2002)
Bar-Joseph, Z., et al.: Computational discovery of gene modules and regulatory networks. Nature Biotechnology 21, 1337–1342 (2003)
Pilpel, Y., et al.: Identifying regulatory networks by combinatorial analysis of promoter elements. Nature Genetics 29, 153–159 (2001)
Tong, A., et al.: Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004)
Tanay, A., et al.: Computational expansion of genetic networks. Bioinformatics 17(suppl. 1), S270–S278 (2001)
Segal, E., et al.: Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nature Genetics 34(2), 166–176 (2003)
Yuh, C., et al.: Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene. Science 279, 1896–1902 (1998)
Lee, T.H., et al.: A transcriptional regulatory network map for Saccharomyces cerevisiae. Science 298, 799–804 (2002)
Yeang, C.H., et al.: Physical network models. Journal of Computational Biology 11(2-3), 243–262 (2004)
Hughes, T., et al.: Functional discovery via a compendium of expression profiles. Cell. 102, 109–126 (2000)
Gasch, A., et al.: Genomic expression programs in the response of yeast cells to environmental changes. Molecular Biology of Cell. 11(12), 4241–4257 (2000)
Ambroziak, J., et al.: INO2 and INO4 gene products, positive regulators of phospholipid biosynthesis in Saccharomyces cerevisiae, form a complex that binds to the INO1 promoter. Journal of Biological Chemistry 269(21), 15344–15349 (1994)
Simon, I., et al.: Serial regulation of transcriptional regulators in the yeast cell cycle. Cell. 106, 697–708 (2001)
Bardwell, L., et al.: Differential regulation of transcription: repression by unactivated mitogen-activated protein kinase Kss1 requires Dig1 and Dig2 proteins. PNAS 95(26), 15400–15405 (1998)
Shenhar, G., et al.: A positive regulator of mitosis, Sok2, functions as a negative regulator of meiosis in Saccharomyces Cerevisiae. Cellular Biology 21(5), 1603–1612 (2001)
Lee, J., et al.: YAP1 and SKN7 control two specialized oxidative stress response regulons in yeast. Journal of Biological Chemistry 274(23), 16040–16046 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yeang, CH., Jaakkola, T. (2005). Modeling the Combinatorial Functions of Multiple Transcription Factors. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2005. Lecture Notes in Computer Science(), vol 3500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415770_39
Download citation
DOI: https://doi.org/10.1007/11415770_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25866-7
Online ISBN: 978-3-540-31950-4
eBook Packages: Computer ScienceComputer Science (R0)