Use of randomized sampling for analysis of metabolic networks.

TitleUse of randomized sampling for analysis of metabolic networks.
Publication TypeJournal Article
Year of Publication2009
AuthorsSchellenberger J, Palsson BØ
JournalThe Journal of biological chemistry
PubMed Date2009 Feb 27
KeywordsAnimals, Computer Simulation, Humans, Metabolic Networks and Pathways, Models, Biological, Monte Carlo Method, Signal Transduction, Systems Biology

Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise in analyzing the systemic properties of these network reconstructions. Notably, constraint-based models have been used successfully to predict the phenotypic effects of knock-outs and for metabolic engineering. The inherent uncertainty in both parameters and variables of large-scale models is significant and is well suited to study by Monte Carlo sampling of the solution space. These techniques have been applied extensively to the reaction rate (flux) space of networks, with more recent work focusing on dynamic/kinetic properties. Monte Carlo sampling as an analysis tool has many advantages, including the ability to work with missing data, the ability to apply post-processing techniques, and the ability to quantify uncertainty and to optimize experiments to reduce uncertainty. We present an overview of this emerging area of research in systems biology.

Alternate JournalJ. Biol. Chem.
PubMed ID18940807



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