Predicting metabolic pathways from metabolic networks with limited biological knowledge
Understanding the metabolism of new species (e.g. endophytic fungi that produce fuel) have tremendous impact on human lives. Based on predicted proteins and existing reaction databases, one can construct the metabolic network for the species. Next is to identify critical metabolic pathways from the...
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Zusammenfassung: | Understanding the metabolism of new species (e.g. endophytic fungi that produce fuel) have tremendous impact on human lives. Based on predicted proteins and existing reaction databases, one can construct the metabolic network for the species. Next is to identify critical metabolic pathways from the network. Existing computational techniques identify conserved pathways based on multiple networks of related species, but have the following drawbacks. Some do not rely on additional information, so only locate short (of length at most 5), but not necessarily interesting, conserved paths. The others require extensive information (the complete pathway on one species). In reality, researchers usually know only partial information of a metabolic pathway and may not have a conserved pathway in a related species. The Conserved Metabolic Pathway (CMP) problem is to find conserved pathways from the networks with partial information on the initial substrates and final products of the target pathways. Experimental results show that our algorithm CMPFinder can predict useful metabolic pathways with acceptable accuracy. |
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DOI: | 10.1109/BIBMW.2010.5703765 |