This article is part of the supplement: Symposium of Computations in Bioinformatics and Bioscience (SCBB06)

Research

Combining comparative genomics with de novo motif discovery to identify human transcription factor DNA-binding motifs

Linyong Mao and W Jim Zheng

Department of Biostatistics, Bioinformatics and Epidemiology, and Bioinformatics Core Facility, Hollings Cancer Center, Medical University of South Carolina, 135 Cannon Street, Charleston, SC 29425, USA

author email corresponding author email

BMC Bioinformatics 2006, 7(Suppl 4):S21doi:10.1186/1471-2105-7-S4-S21

Published:	12 December 2006

Abstract

Background

As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gene regulations.

Results

We developed a novel method to combine comparative genomics with de novo motif discovery to identify human transcription factor binding motifs that are overrepresented and conserved in the upstream regions of a set of co-regulated genes. The method is validated by analyzing a well-characterized muscle specific gene set, and the results showed that our approach performed better than the existing programs in terms of sensitivity and prediction rate.

Conclusion

The newly developed method can be used to extract regulatory signals in co-regulated genes, which can be derived from the microarray clustering analysis.