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- W2133319394 abstract "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/)." @default.
- W2133319394 created "2016-06-24" @default.
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- W2133319394 date "2005-07-01" @default.
- W2133319394 modified "2023-09-30" @default.
- W2133319394 title "Metabolic PathFinding: inferring relevant pathways in biochemical networks" @default.
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- W2133319394 doi "https://doi.org/10.1093/nar/gki437" @default.
- W2133319394 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/1160198" @default.
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