Parameter optimization and sensitivity analysis for large kinetic models using a real-coded genetic algorithm

Gene

Volumn 518, Issue 1, 2013, Pages 84-90

  Tohsato, Yukako ^a   Ikuta, Kunihiko ^a   Shionoya, Akitaka ^a   Mazaki, Yusaku ^a   Ito, Masahiro ^a  

^a RITSUMEIKAN UNIVERSITY   (Japan)

Author keywords

Global parameter sensitivity; Kinetic model; Parameter correlation; Parameter sensitivity; Real coded genetic algorithm

Indexed keywords

PENTOSE PHOSPHATE;

ARTICLE; CORRELATION ANALYSIS; ESCHERICHIA COLI; GENETIC ALGORITHM; GLYCOLYSIS; KINETICS; PARAMETER OPTIMIZATION; PARAMETERS; PRIORITY JOURNAL; REAL CODED GENETIC ALGORITHM; SENSITIVITY ANALYSIS;

ALGORITHMS; COMPUTATIONAL BIOLOGY; ESCHERICHIA COLI K12; GLYCOLYSIS; KINETICS; MODELS, GENETIC; PENTOSE PHOSPHATE PATHWAY;

ESCHERICHIA COLI K12;

EID: 84875374752     PISSN: 03781119     EISSN: 18790038     Source Type: Journal    
DOI: 10.1016/j.gene.2012.11.080     Document Type: Article

References (24)

1. Akimoto Y., Hasada R., Sakuma J., Ono I., Kobayashi S. Generation alternation model for real-coded GA using multi-parent: proposal and evaluation of just generation gap (JGG). Proceeding of the 19th SICE Symposium on Decentralized Autonomous Systems 2007 2007, 341-346.
2. Chassagnole C., Noisommit-Rizzi N., Schmid J.W., Mauch K., Reuss M. Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol. Bioeng. 2002, 79:53-73.
3. Costa R.S., Machado D., Rocha I., Ferreira E.C. Hybrid dynamic modeling of Escherichia coli central metabolic network combining Michaelis-Menten and approximate kinetic equations. Biosystems 2010, 100:150-157.
4. Degenring D., Froemel C., Dikta G., Takors R. Sensitivity analysis for the reduction of complex metabolism models. J. Process Control 2004, 14:729-745.
5. Fang F., Ni B.J., Yu H.Q. Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm. Water Res. 2009, 43:2595-2604.
6. Goldberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning 1989, Addison-Wesley.
7. Ishii N., Nakayama Y., Tomita M. Distinguishing enzymes using metabolome data for the hybrid dynamic/static method. Theor. Biol. Med. Model. 2007, 4:19.
8. Jamal A., Kellett G.L., Robertson J.P. The effect of glucose on the activity of phosphofructokinase in the mucosa of rat small intestine. Biochem. J. 1984, 218:459-464.
9. Kadir T.A., Mannan A.A., Kierzek A.M., McFadden J., Shimizu K. Modeling and simulation of the main metabolism in Escherichia coli and its several single-gene knockout mutants with experimental verification. Microb. Cell Fact. 2010, 9:88.
10. Kita H., Ono I., Kobayashi S. Multi-parental extension of the unimodal normal distribution crossover for real-coded genetic algorithms. Proceedings of IEEE Congress on Evolutionary Computation 1999, 1581-1588.
11. Kobayashi S. The frontiers of real-coded genetic algorithms. Trans. Jpn. Soc. Artif. Intell. 2009, 24:147-162.
12. Lee F.C., Pandu Rangaiah G., Lee D.Y. Modeling and optimization of a multi-product biosynthesis factory for multiple objectives. Metab. Eng. 2010, 12:251-267.
13. Li C., et al. BioModels Database: an enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst. Biol. 2010, 4:92.
14. Maggio J.D., Ricci J.C.D., Diaz M.S. Global sensitivity analysis in dynamic metabolic networks. Comput. Chem. Eng. 2010, 770-781.
15. Matsubara Y., Kikuchi S., Sugimoto M., Tomita M. Parameter estimation for stiff equations of biosystems using radial basis function networks. BMC Bioinformatics 2006, 7:230.
16. Ono I., Kobayashi K. A real coded genetic algorithm for function optimization using unimodal normal distributed crossover. Proceedings of the 7th International Conference on Genetic Algorithms 1997, 246-253.
17. Peng L., Shimizu K. Global metabolic regulation analysis for Escherichia coli K12 based on protein expression by 2-dimensional electrophoresis and enzyme activity measurement. Appl. Microbiol. Biotechnol. 2003, 61:163-178.
18. Satoh H., Yamamura M., Kobayashi S. Minimal generation gap model for GAs considering both exploration and exploitation. Proceedings of IIZUKA '96 1996, 494-497.
19. Schomburg I., et al. BRENDA, the enzyme database: updates and major new developments. Nucleic Acids Res. 2004, 32:D431-D433.
20. Stetak A., Veress R., Ovadi J., Csermely P., Keri G., Ullrich A. Nuclear translocation of the tumor marker pyruvate kinase M2 induces programmed cell death. Cancer Res. 2007, 67:1602-1608.
21. Stryer L. Pentose Phosphate Pathway and Gluconeogenesis 1988, Freeman and Company.
22. Usuda Y., et al. Dynamic modeling of Escherichia coli metabolic and regulatory systems for amino-acid production. J. Biotechnol. 2010, 147:17-30.
23. Wittig U., et al. SABIO-RK-database for biochemical reaction kinetics. Nucleic Acids Res. 2012, 40:D790-D796.
24. Wright B.E., Butler M.H., Albe K.R. Systems analysis of the tricarboxylic acid cycle in Dictyostelium discoideum. I. The basis for model construction. J. Biol. Chem. 1992, 267:3101-3105.