Beyond microarrays: Finding key transcription factors controlling signal transduction pathways

2006 | conference paper. A publication with affiliation to the University of Göttingen.

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​Beyond microarrays: Finding key transcription factors controlling signal transduction pathways​
Kel, A. E.; Voss, N.; Jauregui, R.; Kel-Margoulis, O. & Wingender, E.​ (2006)
BMC Bioinformatics7 ​3rd Annual Conference of the MidSouth-Computational-Biology-and-Bioinformatics-Society​, Baton Rouge, LA.
London​: Biomed Central Ltd. DOI: https://doi.org/10.1186/1471-2105-7-S2-S13 

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Authors
Kel, Alexander E.; Voss, Nico; Jauregui, Ruy; Kel-Margoulis, Olga; Wingender, Edgar
Abstract
Background: Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments. Results: We developed a novel approach to find key transcription factors that may explain concerted expression changes of specific components of the signal transduction network. The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors. We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways. Application of the approach to the microarray gene expression data on TNF-alpha stimulated primary human endothelial cells helped to reveal novel key transcription factors potentially involved in the regulation of the signal transduction pathways of the cells. Conclusion: We developed a novel computational approach for revealing key transcription factors by knowledge-based analysis of gene expression data with the help of databases on gene regulatory networks (TRANSFAC (R) and TRANSPATH (R)). The corresponding software and databases are available at http://www.gene-regulation.com.
Issue Date
2006
Status
published
Publisher
Biomed Central Ltd
Journal
BMC Bioinformatics 
Conference
3rd Annual Conference of the MidSouth-Computational-Biology-and-Bioinformatics-Society
Conference Place
Baton Rouge, LA
ISSN
1471-2105

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