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Nucleic Acids Research 2005 33(Web Server Issue):W326-W330; doi:10.1093/nar/gki437
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© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oupjournals.org


Article

Metabolic PathFinding: inferring relevant pathways in biochemical networks

Didier Croes, Fabian Couche, Shoshana J. Wodak and Jacques van Helden*

SCMBB, Université Libre de Bruxelles Campus Plaine, CP 263, Boulevard du Triomphe, B-1050 Bruxelles, Belgium

*To whom correspondence should be addressed. Tel: +32 2 650 5466; Fax: +32 2 650 5425; Email: jvanheld{at}scmbb.ulb.ac.be

Received February 14, 2005. Revised March 25, 2005. Accepted March 25, 2005.

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).


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