Abstract
A modelling framework that consists of model building, validation and analysis, leading to model-based design of experiments and to the application of optimisation-based model-predictive control strategies for the development of optimised bioprocesses is presented. An example of this framework is given with the construction and experimental validation of a dynamic mathematical model of the Ps/Pr promoters system of the TOL plasmid, which is used for the metabolism of m -xylene by Pseudomonas putida mt-2. Furthermore, the genetic circuit model is combined with the growth kinetics of the strain in batch cultures, demonstrating how the description of key genetic circuits can facilitate the improvement of existing growth kinetic models that fail to predict unusual growth patterns. Consequently, the dynamic model is combined with global sensitivity analysis, which is used to identify the presence of significant model parameters, constituting a model-based methodology for the formulation of genetic circuit optimization methods.
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