Parameter Estimation in Kinetic Models for Large Scale Metabolic Networks with Advanced Mathematical Programming Techniques

摘要

In this work, we formulate a parameter estimation problem for a large-scale dynamicrnmetabolic network. The DAE system represents the dynamic model for the Embden-rnMeyerhof-Parnas pathway, the phosphotransferase system and the pentose-phosphaternpathway of Escherichia coli K-12 W3110 (Chassagnole et al., 2002), withrnmodifications on several enzyme kinetics and the addition of fermentation reactions.rnModel parameters have been estimated based on recently published experimental datarnfor this strain. Most sensitive parameters have been ranked by performing globalrnsensitivity analysis on the dynamic metabolic network (Di Maggio et al., 2009a,b).rnEleven kinetic parameters, including maximum reaction rates, inhibition and halfsaturationrnconstants, have been estimated with good agreement with availablernexperimental data.