Title
PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences.
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.
Year
DOI
Venue
2004
10.1186/1471-2105-5-170
BMC Bioinformatics
Keywords
Field
DocType
expectation maximization,probabilistic algorithm,transcription factor binding site,bioinformatics,phylogeny,dna,microarrays,synthetic data,algorithms,phylogenetic tree
Randomized algorithm,Gene,DNA binding site,Biology,Expectation–maximization algorithm,Homology (biology),Bioinformatics,Phylogenetics,Genetics,DNA microarray,Regulatory sequence
Journal
Volume
Issue
ISSN
5
1
1471-2105
Citations 
PageRank 
References 
68
4.15
12
Authors
3
Name
Order
Citations
PageRank
Saurabh Sinha152948.96
Mathieu Blanchette263162.65
Martin Tompa31103149.69