Associating transcription factor-binding site motifs with target GO terms and target genes

Boden, M. and Bailey, T. L. (2008) Associating transcription factor-binding site motifs with target GO terms and target genes. Nucleic Acids Research, 36 12: 4108-4117. doi:10.1093/nar/gkn374


Author Boden, M.
Bailey, T. L.
Title Associating transcription factor-binding site motifs with target GO terms and target genes
Journal name Nucleic Acids Research   Check publisher's open access policy
ISSN 0305-1048
1362-4954
Publication date 2008-06-10
Year available 2008
Sub-type Article (original research)
DOI 10.1093/nar/gkn374
Open Access Status DOI
Volume 36
Issue 12
Start page 4108
End page 4117
Total pages 10
Editor R. J. Roberts
K. R. Fox
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Subject C1
060405 Gene Expression (incl. Microarray and other genome-wide approaches)
970106 Expanding Knowledge in the Biological Sciences
Abstract The roles and target genes of many transcription factors (TFs) are still unknown. To predict the roles of TFs, we present a computational method for associating Gene Ontology (GO) terms with TF-binding motifs. The method works by ranking all genes as potential targets of the TF, and reporting GO terms that are significantly associated with highly ranked genes. We also present an approach, whereby these predicted GO terms can be used to improve predictions of TF target genes. This uses a novel genescoring function that reflects the insight that genes annotated with GO terms predicted to be associated with the TF are more likely to be its targets. We construct validation sets of GO terms highly associated with known targets of various yeast and human TF. On the yeast reference sets, our prediction method identifies at least one correct GO term for 73% of the TF, 49% of the correct GO terms are predicted and almost one-third of the predicted GO terms are correct. Results on human reference sets are similarly encouraging. Validation of our target gene prediction method shows that its accuracy exceeds that of simple motif scanning.
Keyword Transcription factors (TFs)
Gene Ontology (GO)
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID R0-1 RR021692-01
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: 2009 Higher Education Research Data Collection
 
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Created: Tue, 07 Apr 2009, 01:00:57 EST by Cody Mudgway on behalf of Institute for Molecular Bioscience