Mathematical modelling of cellular metabolism plays an important role in understandingbiological functions and providing identification of targets for biotechnological modification.This paperproposes a nonlinear bilev...Mathematical modelling of cellular metabolism plays an important role in understandingbiological functions and providing identification of targets for biotechnological modification.This paperproposes a nonlinear bilevel programming(NBP)model to infer the objective function of anaerobicglycerol metabolism in Klebsiella Pneumoniae(K.Pneumoniae)for 1,3-propanediol(1,3-PD)production.Based on the Kuhn-Tucker optimality condition of the lower level problem,NBP is transformedinto a nonlinear programming with complementary and slackness conditions.The authors give the existencetheorem of solutions to NBP.An efficient algorithm is proposed to solve NBP and its convergenceis also simply analyzed.Numerical results reveal some interesting conclusions,e.g.,biomass productionis the main force to drive glycerol metabolism,and the objective functions,which are obtained in termof several different groups of flux distributions,are similar.展开更多
The bioconversion of glycerol to 1,3-propanediol is a complex bioprocess. The item of product inhibition in the equation of Specific rate of cell growth is overlapped in [L. Wang, J. X. Ye, E. M. Feng and Z. L. Xiu, A...The bioconversion of glycerol to 1,3-propanediol is a complex bioprocess. The item of product inhibition in the equation of Specific rate of cell growth is overlapped in [L. Wang, J. X. Ye, E. M. Feng and Z. L. Xiu, An improved model for multistage simula- tion of glycerol fermentation in batch culture and its parameter identification, Nonlinear Anal. Hybrid Syst. 3（4） （2009） 455462]. Therefore, in this work, the specific rate of cell growth is modified by the mechanism of multistage simulation of microbial bioconversion and the previous time-dependent model is converted to the autonomous standard form. The properties of the solutions for the nonlinear dynamic system are discussed and the identifiability of the parameters is proved. Finally the feasible optimization algorithm is constructed to find the optimal parameters for the system. Numerical result shows that the improved model with identified parameters can describe the batch culture better, compared with the previous results.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.10871033 and 10671126
文摘Mathematical modelling of cellular metabolism plays an important role in understandingbiological functions and providing identification of targets for biotechnological modification.This paperproposes a nonlinear bilevel programming(NBP)model to infer the objective function of anaerobicglycerol metabolism in Klebsiella Pneumoniae(K.Pneumoniae)for 1,3-propanediol(1,3-PD)production.Based on the Kuhn-Tucker optimality condition of the lower level problem,NBP is transformedinto a nonlinear programming with complementary and slackness conditions.The authors give the existencetheorem of solutions to NBP.An efficient algorithm is proposed to solve NBP and its convergenceis also simply analyzed.Numerical results reveal some interesting conclusions,e.g.,biomass productionis the main force to drive glycerol metabolism,and the objective functions,which are obtained in termof several different groups of flux distributions,are similar.
文摘The bioconversion of glycerol to 1,3-propanediol is a complex bioprocess. The item of product inhibition in the equation of Specific rate of cell growth is overlapped in [L. Wang, J. X. Ye, E. M. Feng and Z. L. Xiu, An improved model for multistage simula- tion of glycerol fermentation in batch culture and its parameter identification, Nonlinear Anal. Hybrid Syst. 3（4） （2009） 455462]. Therefore, in this work, the specific rate of cell growth is modified by the mechanism of multistage simulation of microbial bioconversion and the previous time-dependent model is converted to the autonomous standard form. The properties of the solutions for the nonlinear dynamic system are discussed and the identifiability of the parameters is proved. Finally the feasible optimization algorithm is constructed to find the optimal parameters for the system. Numerical result shows that the improved model with identified parameters can describe the batch culture better, compared with the previous results.
