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  Functional inference from non-random distributions of conserved predicted transcription factor binding sites

Dieterich, C., Rahmann, S., & Vingron, M. (2004). Functional inference from non-random distributions of conserved predicted transcription factor binding sites. Bioinformatics, 20(Suppl.), i109-i115.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-88B7-4 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-88B8-2
Genre: Conference Paper

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 Creators:
Dieterich, Christoph1, Author
Rahmann, Sven2, Author              
Vingron, Martin3, Author              
Affiliations:
1Max Planck Society, ou_persistent13              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
3Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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 Abstract: Motivation: Our understanding of how genes are regulated in a concerted fashion is still limited. Especially, complex phenomena like cell cycle regulation in multicellular organisms are poorly understood. Therefore, we investigated conserved predicted transcription factor binding sites (TFBSs) in man–mouse upstream regions of genes that can be associated to a particular cell cycle phase in HeLa cells. TFBSs were predicted from selected binding site motifs (represented by position weight matrices, PWMs) based on a statistical approach. A regulatory role for a transcription factor is more probable if its predicted TFBSs are enriched in upstream regions of genes, that are associated with a subset of cell cycle phases. We tested for this association by computing exact P-values for the observed phase distributions under the null distribution defined by the relative amount of conserved upstream sequence of genes per cell cycle phase. We considered non-exonic and 5'-untranslated region (5'-UTR) binding sites separately and corrected for multiple testing by taking the false discovery rate into account. Results: We identified 22 non-exonic and 11 5'-UTR significant PWM phase distributions although expecting one false discovery. Many of the corresponding transcription factors (e.g. members of the thyroid hormone/retinoid receptor subfamily) have already been associated with cell cycle regulation, proliferation and development. It appears that our method is a suitable tool for detecting putative cell cycle regulators in the realm of known human transcription factors.

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Language(s): eng - English
 Dates: 2004-03-01
 Publication Status: Published in print
 Pages: -
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 Identifiers: eDoc: 226444
DOI: 10.1093/bioinformatics/bth908
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Title: Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology
Place of Event: Glasgow, UK
Start-/End Date: 2004-07-31 - 2004-08-04

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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 20 (Suppl.) Sequence Number: - Start / End Page: i109 - i115 Identifier: ISSN: 1460-2059