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Published Online: 18 August 2005

Identifying Conserved Gene Clusters in the Presence of Homology Families

Publication: Journal of Computational Biology
Volume 12, Issue Number 6

Abstract

The study of conserved gene clusters is important for understanding the forces behind genome organization and evolution, as well as the function of individual genes or gene groups. In this paper, we present a new model and algorithm for identifying conserved gene clusters from pairwise genome comparison. This generalizes a recent model called "gene teams." A gene team is a set of genes that appear homologously in two or more species, possibly in a different order yet with the distance of adjacent genes in the team for each chromosome always no more than a certain threshold. We remove the constraint in the original model that each gene must have a unique occurrence in each chromosome and thus allow the analysis on complex prokaryotic or eukaryotic genomes with extensive paralogs. Our algorithm analyzes a pair of chromosomes in O(mn) time and uses O(m+n) space, where m and n are the number of genes in the respective chromosomes. We demonstrate the utility of our methods by studying two bacterial genomes, E. coli K-12 and B. subtilis. Many of the teams identified by our algorithm correlate with documented E. coli operons, while several others match predicted operons, previously suggested by computational techniques. Our implementation and data are publicly available at euler.slu.edu/∼goldwasser/homologyteams/.

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Published In

cover image Journal of Computational Biology
Journal of Computational Biology
Volume 12Issue Number 6July/August 2005
Pages: 638 - 656
PubMed: 16108708

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Published online: 18 August 2005
Published in print: July/August 2005

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Xin He
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Michael H. Goldwasser
Department of Mathematics and Computer Science, Saint Louis University, St. Louis, MO 63103-2007.

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