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PMID: 15511292 Published · epublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S.

PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences.

BMC bioinformatics ·Vol. 5 ·2004-10-28 ·Pages 170

Sinha S, Blanchette M, Tompa M

Abstract

This paper addresses the problem of discovering transcription factor binding sites in heterogeneous sequence data, which includes regulatory sequences of one or more genes, as well as their orthologs in other species. We propose an algorithm that integrates two important aspects of a motif's significance - overrepresentation and cross-species conservation - into one probabilistic score. The algorithm allows the input orthologous sequences to be related by any user-specified phylogenetic tree. It is based on the Expectation-Maximization technique, and scales well with the number of species and the length of input sequences. We evaluate the algorithm on synthetic data, and also present results for data sets from yeast, fly, and human. The results demonstrate that the new approach improves motif discovery by exploiting multiple species information.

MeSH Terms
Algorithms Animals Base Composition/genetics DNA/genetics DNA, Fungal/genetics Drosophila/genetics Drosophila melanogaster/genetics Enhancer Elements, Genetic/genetics Evolution, Molecular Humans Models, Genetic Phylogeny Saccharomyces/genetics Saccharomyces cerevisiae/genetics Software Species Specificity
Chemicals
DNA, Fungal DNA
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Sinha Saurabh
Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA. [email protected]
Blanchette Mathieu
Tompa Martin
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Article Info
Journal
BMC bioinformatics
Abbr.
BMC Bioinformatics
ISSN
1471-2105
Published
2004-10-28
Epub
2004-00-28
Pages
170
Language
English
Region
England
NLM ID
100965194
PMCID
PMC534098
Subset
IM
Grants
NHGRI NIH HHS · R01 HG002602 · United States
NHGRI NIH HHS · R01 HG02602 · United States
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