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Bioinformatics Advance Access originally published online on May 31, 2007
Bioinformatics 2007 23(15):2013-2014; doi:10.1093/bioinformatics/btm282
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Tree Gibbs Sampler: identifying conserved motifs without aligning orthologous sequences

Xiaohui Cai 1,2, Haiyan Hu 2 and Xiaoman Shawn Li 1,2,*

1Division of Biostatistics and 2Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, 410 West 10th Street, Indianapolis, IN 46202, USA

*To whom correspondence should be addressed.


  Abstract

Summary: Tree Gibbs Sampler is a software for identifying motifs by simultaneously using the motif overrepresentation property and the motif evolutionary conservation property. It identifies motifs without depending on pre-aligned orthologous sequences, which makes it useful for the extraction of regulatory elements in multiple genomes of both closely related and distant species.

Availability: The Tree Gibbs Sampler software is freely downloadable at https://compbio.iupui.edu/xiaomanli/LiSoftware/retrieve.php?ID=tgs

Contact: shawnli{at}iupui.edu

Associate Editor: Alfonso Valencia

Received on February 3, 2007; revised on April 17, 2007; accepted on May 18, 2007

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