Reconstructing metabolic pathways by bidirectional chemical search

Authors:
Liliana Félix;Francesc Rosselló;Gabriel Valiente
Affiliations:
Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, Barcelona, Spain;Department of Mathematics and Computer Science, University of the Balearic, Islands, Palma de Mallorca;Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, Barcelona, Spain
Venue:
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Year:
2007

Citing 4
Cited 0

Artificial chemistries—a review

Artificial Life
Representing, Analyzing, and Synthesizing Biochemical Pathways

IEEE Expert: Intelligent Systems and Their Applications
Chemical Graphs, Chemical Reaction Graphs, and Chemical Graph Transformation

Electronic Notes in Theoretical Computer Science (ENTCS)
Graph transformation in molecular biology

Formal Methods in Software and Systems Modeling

Quantified Score

Hi-index	0.00

Visualization

Abstract

One of the main challenges in systems biology is the establishment of the metabolome: a catalogue of the metabolites and bio-chemical 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.