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Bioinformatics Advance Access published online on June 28, 2005

Bioinformatics, doi:10.1093/bioinformatics/bti554
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received September 7, 2004
Revised January 6, 2005
Accepted January 11, 2005

Article

Alignment of metabolic pathways

Ron Y. Pinter 1*, Oleg Rokhlenko 1, Esti Yeger-Lotem 1, and Michal Ziv-Ukelson 1

1 Dept. of Computer Science, Technion - Israel Institute of Technology, Haifa 32000, Israel

* To whom correspondence should be addressed.
Ron Y. Pinter, E-mail: pinter{at}cs.technion.ac.il


   Abstract

Motivation: Several genome-scale efforts are underway to reconstruct metabolic networks for a variety of organisms. As the resulting data accumulates, the need for analysis tools increases. A notable requirement is a pathway alignment finder that enables both the detection of conserved metabolic pathways among different species as well as divergent metabolic pathways within a species. When comparing two pathways, the tool should be powerful enough to take into account both the pathway topology as well as the nodes' labels (e.g. the enzymes they denote), and allow flexibility by matching similar -- rather than identical -- pathways.

Results: MetaPathwayHunter is a pathway alignment tool that, given a query pathway and a collection of pathways, finds and reports all approximate occurrences of the query in the collection, ranked by similarity and statistical significance. It is based on a novel, efficient graph matching algorithm that extends the functionality of known techniques. The program also supports a visualization interface with which the alignment of two homologous pathways can be graphically displayed.

We employed this tool to study the similarities and differences in the metabolic networks of the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae, as represented in highly curated databases. We reaffirmed that most known metabolic pathways common to both species are conserved. Furthermore, we discovered a few intriguing relationships between pathways that provide insight into the evolution of metabolic pathways. We conclude with a description of biologically meaningful meta-queries, demonstrating the power and flexibility of our new tool in the analysis of metabolic pathways.

Availability: Code and data upon request.


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