SENSITIVITY FUNCTION BASED MODEL REDUCTION: A BACTERIAL GENE EXPRESSION CASE STUDY
Ilse Smets* Kristel Bernaerts* Jun Sun** Kathleen Marchal***Jos Vanderleyden** Jan Van Impe*
* BioTeCKatholieke Universiteit Leuven, B-3001 Leuven (Belgium) Fax: +32-16-32.19.60 e-mail: jan.vanimpe@agr.kuleuven.ac.be
** CMPG-Katholieke Universiteit Leuven, B-3001 Leuven (Belgium)
*** ESAT-Katholieke Universiteit Leuven, B-3001 Leuven (Belgium)
In the area of genetically engineered micro-organisms grown in bioreactors, mathematical modeling usually results in balance type models involving (i) a (rather) large number of state variables and, (ii) complicated kinetic expressions containing a large number of parameters. Therefore, a generic methodology is developed to reduce the model complexity at the level of the kinetics, while maintaining high prediction power. As a case study to illustrate the method and results obtained, the influence of the dissolved oxygen concentration on the cytN gene expression in the bacterium Azospirillum brasilense Sp7 is modeled.
Keywords: modelling, model reduction, sensitivity functions, biotechnology, continuous systems
Session slot T-Tu-M13: Dynamics and Control of Bioprocesses/Area code 7d : Control of Biotechnological Processes

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