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Submitted on March 9, 2004
Accepted on November 17, 2004
Center for Genomics and Bioinformatics, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine and Therapeutics, BC Children's and Women's Hospitals, Vancouver, Canada; Department of Medical Genetics, University of British Columbia, Vancouver Canada
* To whom correspondence should be addressed. E-mail: wyeth{at}cmmt.ubc.ca.
The nuclear receptor class of transcription factors controls critical regulatory events in key developmental processes, homeostasis maintenance and medically important diseases and conditions. Identification of the members of a regulon controlled by a nuclear receptor could provide an accelerated understanding of development and disease. New bioinformatics methods for the analysis of regulatory sequences are required to address the complex properties associated with known regulatory elements targeted by the receptors, as the standard methods for binding site prediction fail to reflect the diverse target site configurations. We have constructed a flexible Hidden Markov Model framework capable of predicting nuclear hormone receptor binding sites. The model allows for variable spacing and orientation of half-sites. In a genome-scale analysis enabled by the model, we show that nuclear receptors in Fugu rubripes have a significant cross-regulatory potential. The model is implemented in a web interface, freely available for academic researchers, available at http://mordor.cgb.ki.se/NHR-scan.
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