PMID:22021171

Citation	Tan, Y and Liao, JC (2012) Metabolic ensemble modeling for strain engineers. Biotechnol J 7:343-53
Abstract	Previous mathematical modeling efforts have made significant contributions to the development of systems biology for predicting biological behavior quantitatively. However, dynamic metabolic model construction remains challenging due to uncertainties in mechanistic structures and parameters. In addition, parameter estimation and model validation often require designated experiments conducted only for purpose of modeling. Such difficulties have hampered the progress of modeling in biology and biotechnology. To circumvent these problems, ensemble approaches have been used to account for uncertainties in model structure and parameters. Specifically, this review focuses on approaches that utilize readily available fermentation data for parameter screening and model validation. Time course data for metabolite measurements, if available, can further calibrate the model. The basis for this approach is explained in non-mathematical terms accessible to experimentalists. Information gained from such an approach has been shown to be useful in designing Escherichia coli strains for metabolic engineering and synthetic biology.
Links	PubMed Online version:10.1002/biot.201100186
Keywords	Computer Simulation; Escherichia coli/genetics; Humans; Metabolic Engineering/methods; Metabolic Networks and Pathways; Models, Theoretical; Systems Biology/methods
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