Abstract
Different objective functions in the dynamic model can explore the diverse properties of the solution space, and a wide variety of capabilities of an organism. In that way, when there is a fact that several conditions can simultaneously achieve the optimality, the multiple objective functions are explored in the dynamic model of metabolic networks naturally. For obtaining the better simulation consequences of the concentrations of glucose and biomass in the metabolism of Escherichia coli, we choose both of the maximal biomass yield and maximal glucose utilization ratio to structure the multiple objective functions. The simulation results of the metabolite concentrations agree well with the experimental results.
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References
Fell, D.: Understanding the Control of Metabolism. Portland Press, London (1996)
Savageau, M.A., Voit, E.O., Irine, D.H.: Biochemical Systems Theory and Metabolic Control Theory: 1. Fundamental Similarities and Differences. Math. Biosci. 86, 127–145 (1987)
Savageau, M.A., Voit, E.O., Irine, D.H.: Biochemical Systems Theory and Metabolic Control Theory: 2. The Role of Summation and Connectivity Relationships. Math. Biosci. 86, 147–169 (1987)
Amit, V., Bemhard, O.P.: Stoichiometric Flux Balance Models Quantitatively Predict Growth and Metabolic by-product Secretion in Wild-Type Escherichia ColiW3110. Appl. Environ. Microbiol. 60, 3724–3731 (1994)
Mahadevan, R., Edwards, J.S., Doyle, F.J.: Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli. Biophy. J. 83, 1331–1340 (2002)
Zhou, Q.H., Wang, D., Xiong, M.M.: Dynamic Flux Balance Analysis of Metabolic Networks Using the Penalty Function Method. In: Proc. of 2007 International Conference on Systems, Man and Cybernetics, Montreal, Canada, October 7-10, pp. 3594–3599 (2007)
Zhou, Q.H., Cui, J., Xie, J.: Solving the Dynamic Model of Metabolic Network of Escherichia coli by Adams Methods. Advanced Materials Research 424-425, 900–903 (2012)
Kompala, D.S.: Bacterial Growth on Multiple Substrates. Experimental Verification of Cybernetic Models, Ph. D Thesis, Purdue University, West Lafayette, IN (1984)
Varner, J., Ramkrishna, D.: Metabolic Engineering from A Cybernetic Perspective I. Theoretical Preliminaries. Biotechnol. Prog. 15, 407–425 (1999)
Huang, P.: Optimal Theories and Methods, pp. 120–123. Qinghua University Press (2009)
Schuetz, R., Kuepfer, L., Sauer, U.: Systematic Evaluation of Objective Functions for Predicting Intracellular Fluxes in Escherichia coli. Bayer Technology Services, Germany (2007)
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Zhou, QH., Cui, J., Xie, J. (2012). Using Multiple Objective Functions in the Dynamic Model of Metabolic Networks of Escherichia coli . In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_20
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DOI: https://doi.org/10.1007/978-3-642-31576-3_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31575-6
Online ISBN: 978-3-642-31576-3
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