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Nucleic Acids Research 2005 33(1):272-279; doi:10.1093/nar/gki167
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Published online 12 January 2005

© 2005, the authors Nucleic Acids Research, Vol. 33 No. 1 © Oxford University Press 2005; all rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions{at}oupjournals.org.

Article

Inferring combinatorial regulation of transcription in silico

Nils Blüthgen*, Szymon M. Kielbasa and Hanspeter Herzel

Humboldt University, Institute for Theoretical Biology Invalidenstrasse 43, 10115 Berlin, Germany

*To whom correspondence should be addressed. Tel: +49 30 2093 9112; Fax: +49 30 2093 8801; Email: nils.bluethgen{at}itb.biologie.hu-berlin.de

Received September 5, 2004. Revised November 3, 2004. Accepted December 15, 2004.

In this paper, we propose a functional view on the in silico prediction of transcriptional regulation. We present a method to predict biological functions regulated by a combinatorial interaction of transcription factors. Using a rigorous statistic, this approach intersects the presence of transcription factor binding sites in gene upstream sequences with Gene Ontology terms associated with these genes. We demonstrate that for the well-studied set of skeletal muscle-related transcription factors Myf-2, Mef and TEF, the correct functions are predicted. Furthermore, starting from the well-characterized promoter of a gene expressed upon lipopolysaccharide stimulation, we predict functional targets of this stimulus. These results are in excellent agreement with microarray data.

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors


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