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Parameter estimation in kinetic models for large scale biotechnological systems with advanced mathematical programming techniques

Paper ID Volume ID Publish Year Pages File Format Full-Text
3196 156 2014 12 PDF Available
Title
Parameter estimation in kinetic models for large scale biotechnological systems with advanced mathematical programming techniques
Abstract

•Dynamic constrained parameter estimation problems for biotechnological systems.•Kinetic parameters adjustment for in vivo conditions.•Control vector parameterization approach.

In the present work, we formulate parameter estimation problems for kinetic models of large-scale dynamic biotechnological systems. We propose dynamic models of increasing complexity for metabolic networks and continuous bioreactors. The differential algebraic equations (DAE) system for the metabolic network represent the glycolysis, the phosphotransferase system and the pentose-phosphate pathway of Escherichia coli, with modifications proposed for several enzyme kinetics. The most sensitive parameters have been ranked by performing global sensitivity analysis on the dynamic metabolic network. Since the kinetic parameters for the enzymes have been obtained from in vitro experiments, the formulation of a detailed kinetic model for the metabolic network allows parameter adjustment for in vivo conditions. We formulate an unstructured non-segregated model for a chemostat to study the dynamic response to a glucose pulse in a continuous culture of E. coli. Moreover, we perform parameter estimation by formulating a maximum likelihood problem, subject to the DAE systems, within a control vector parameterization approach. Nine kinetic parameters in the metabolic network model have been estimated with good agreement with published experimental data. For the bioreactor model, seven parameters have been tuned based on experimental data obtained in this work. Numerical results show a good agreement between the observed data and the predicted profiles.

Keywords
Dynamic metabolic network; Dynamic optimization; Control vector parameterization
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Parameter estimation in kinetic models for large scale biotechnological systems with advanced mathematical programming techniques
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biochemical Engineering Journal - Volume 83, 15 February 2014, Pages 104–115
Authors
, , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us