Formulating genome-scale kinetic models in the post-genome era.

TitleFormulating genome-scale kinetic models in the post-genome era.
Publication TypeJournal Article
Year of Publication2008
AuthorsJamshidi N, Palsson BØ
JournalMolecular systems biology
Volume4
Pagination171
PubMed Date2008
ISSN1744-4292
KeywordsAlgorithms, Computational Biology, Computer Simulation, Genome, Genomics, Glycolysis, Kinetics, Models, Biological, Models, Theoretical, Systems Biology, Thermodynamics, Time Factors
Abstract

The biological community is now awash in high-throughput data sets and is grappling with the challenge of integrating disparate data sets. Such integration has taken the form of statistical analysis of large data sets, or through the bottom-up reconstruction of reaction networks. While progress has been made with statistical and structural methods, large-scale systems have remained refractory to dynamic model building by traditional approaches. The availability of annotated genomes enabled the reconstruction of genome-scale networks, and now the availability of high-throughput metabolomic and fluxomic data along with thermodynamic information opens the possibility to build genome-scale kinetic models. We describe here a framework for building and analyzing such models. The mathematical analysis challenges are reflected in four foundational properties, (i) the decomposition of the Jacobian matrix into chemical, kinetic and thermodynamic information, (ii) the structural similarity between the stoichiometric matrix and the transpose of the gradient matrix, (iii) the duality transformations enabling either fluxes or concentrations to serve as the independent variables and (iv) the timescale hierarchy in biological networks. Recognition and appreciation of these properties highlight notable and challenging new in silico analysis issues.

Alternate JournalMol. Syst. Biol.
PubMed ID18319723

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