title: Efficient reconstruction of metabolic pathways by bidirectional chemical search.
abstract: One of the main challenges in systems biology is the establishment of the metabolome: a catalogue of the metabolites and biochemical reactions present in a specific organism. Current knowledge of biochemical pathways as stored in public databases such as KEGG, is based on carefully curated genomic evidence for the presence of specific metabolites and enzymes that activate particular biochemical reactions. In this paper, we present an efficient method to build a substantial portion of the artificial chemistry defined by the metabolites and biochemical reactions in a given metabolic pathway, which is based on bidirectional chemical search. Computational results on the pathways stored in KEGG reveal novel biochemical pathways.
authors.affiliation: Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, 08034, Barcelona, Spain. lfelix@lsi.upc.edu
authors.forename: Liliana
authors.initials: L
authors.lastname: Félix
authors.forename: Francesc
authors.initials: F
authors.lastname: Rosselló
authors.forename: Gabriel
authors.initials: G
authors.lastname: Valiente
mesh_terms: D000465:Algorithms; D053858:Metabolic Networks and Pathways; D055442:Metabolome; D008954:Models, Biological