Ensemble kinetic modeling of metabolic networks from dynamic metabolic profiles.

ABSTRACT: Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, inst

SUBMITTER: Jia G 

PROVIDER: S-EPMC3901226 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature