Reverse engineering of biochemical equations from time-course data by means of genetic programming

BioSystems

Volumn 80, Issue 2, 2005, Pages 155-164

  Sugimoto, Masahiro ^a,b   Kikuchi, Shinichi ^a   Tomita, Masaru ^a  

^a KEIO UNIVERSITY   (Japan)

^b MITSUBISHI SPACE SOFTWARE CO LTD   (Japan)

Author keywords

Biochemical equation; Genetic programming; Reverse engineering

Indexed keywords

6 PHOSPHOFRUCTOKINASE; ADENYLATE KINASE;

NUMERICAL MODEL;

ARTICLE; BIOCHEMISTRY; CATALYSIS; ERROR; GENE MUTATION; GENETIC ENGINEERING; MATHEMATICAL MODEL; PREDICTION; SIMULATION;

EID: 17044395470     PISSN: 03032647     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystems.2004.11.003     Document Type: Article

References (52)

1. S. Ando, E. Sakamoto, and H. Iba Evolutionary modeling and inference of gene network Inform. Sci. 145 2002 237 259
2. P.J. Angeline Advances in Genetic Programming 2 1996 MIT Press Cambridge, MA pp. 467-488
3. W. Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone Genetic Programming - An Introduction 1998 Morgan Kaufmann San Francisco
4. P. Baumann, and E. Wright The phosphofructokinase of Dictyostelium discoideum Biochemistry 7 1968 3653 3661
5. C.J. Biesheuvel, I. Siccama, D.E. Grobbee, and K.G. Moons Genetic programming outperformed multivariable logistic regression in diagnosing pulmonary embolism J. Clin. Epidemiol. 57 2004 551 560
6. C.C. Bojarczuk, H.S. Lopes, A.A. Freitas, and E.L. Michalkiewicz A constrained-syntax genetic programming system for discovering classification rules: application to medical data sets Artif. Intell. Med. 30 2004 27 48
7. J.J. Cheema, N.V. Sankpal, S.S. Tambe, and B.D. Kulkarni Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation Biotechnol. Prog. 18 2002 1356 1365
8. I. Christian, and C. Kumar Investigating the influence of depth and degree of genotypic change on fitness in genetic programming Proceedings of the Genetic and Evolutionary Computation Conference 1999 1061 1068
9. A. Cornish-Bowden Fundamentals of Enzyme Kinetics third ed. 2004 Portland Press London
10. J. Eggermont, and J.I. Hemert Stepwise adaptation of weights for symbolic regression with genetic programming Proceedings of the Belgium/Netherlands Conference on Artificial Intelligence 2000 259 266
11. M. Evett, and T. Fernandez Numeric mutation improves the discovery of numeric constants in genetic programming Proceedings of the Genetic and Evolutionary Computation Conference 1998 66 71
12. D.B. Fogel, and J.W. Atmar Comparing genetic operators with gaussian mutations in simulated evolutionary processes using linear systems Bio. Cybern. 63 1990 111 114
13. R.J. Gilbert, R. Goodacre, A.M. Woodward, and D.B. Kell Genetic programming: a novel method for the quantitative analysis of pyrolysis mass spectral data Anal. Chem. 69 1997 4381 4389
14. A. Gilman, and J. Ross Genetic-algorithm selection of a regulatory structure that directs flux in a simple metabolic model Biophys. J. 69 1995 1321 1333
15. D.E. Goldberg Genetic Algorithms in Search, Optimization and Machine Learning 1989 Addison-Wesley Reading, MA
16. H.F. Gray, R.J. Maxwell, I. Martinez-Perez, C. Arus, and S. Cerdan Genetic programming for classification and feature selection: analysis of 1H nuclear magnetic resonance spectra from human brain tumour biopsies NMR Biomed. 11 1998 214 217
17. M. Hatakeyama, S. Kimura, T. Naka, T. Kawasaki, N. Yumoto, M. Ichikawa, J. Kim, K. Saito, M. Kaeki, M. Sirouzu, S. Yokoyama, and A. Konagaya A computational model on the modulation of mitogen-activated protein kinase (MAPK) and Akt pathways in heregulin-induced ErbB signalling Biochem. J. 373 2003 451 463
18. J.H. Holland Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence 1975 University of Michigan Press Ann Arbor p. 183
19. J.H. Hong, and S.B. Cho Lymphoma cancer classification using genetic programming with SNR features Proceedings of the Genetic Programming European Conference 2004 78 88
20. Y.J. Hu GPRM: a genetic programming approach to finding common RNA secondary structure elements Nucleic Acids Res. 31 2003 3446 3449
21. T. Ito, and S. Sato Non-destructive depth-dependent crossover for genetic programming Proceedings of the European Workshop on Genetic Programming 1998 71 82
22. D.B. Kell, R.M. Darby, and J. Draper Genomic computing Explanatory analysis of plant expression profiling data using machine learning Plant Physiol. 126 2001 943 951
23. S. Kikuchi, D. Tominaga, M. Arita, K. Takahashi, and M. Tomita Dynamic modeling of genetic networks using genetic algorithm and S-system Bioinformatics 18 2003 643 650
24. J.R. Koza Genetic Programming, on the Programming of Computers by Means of Natural Selection 1992 MIT Press Cambridge, MA
25. J.R. Koza Genetic Programming II: Automatic Discovery of Reusable Programs 1994 MIT Press Cambridge, MA
26. J.R. Koza, F.H. Bennett, M.A. Keane, and D. Andre Genetic Programming III: Darwinian Invention and Problem Solving 1999 Morgan Kaufmann San Francisco
27. Koza, J.R, Mydlowec, W., Lanza, G., Yu, J., Keane, M.A., 2000. Reverse engineering and automatic synthesis of metabolic pathways from observed data using genetic programming. Stanford Medical Informatics Technical Report SMI-2000-0851.
28. J.R. Koza, W. Mydlowec, G. Lanza, J. Yu, and M. Keane Reverse engineering of metabolic pathways from observed data using genetic programming Pac. Symp. Biocomput. 2001 434 445
29. J.R. Koza Engineering Design Synthesis 2002 Springer London pp. 319-337
30. J.R. Koza, M.A. Keane, M.J. Streeter, W. Mydlowec, J. Yu, and G. Lanza Genetic Programming IV: Routine Human-Competitive Machine Intelligence 2003 Kluwer Academic Publishers New York
31. Z. Kutalik, K.H. Cho, and O. Wolkenhauer Optimal sampling time selection for parameter estimation in dynamic pathway modeling BioSystems 75 2004 43 55
32. W.B. Langdon, and B.F. Buxton Genetic programming for mining DNA chip data from cancer patients Genet. Programming Evolvable Mach. 5 2004 251 257
33. H.H. McAdams, and A. Arkin It's a noisy business! Genetic regulation at the nanomolar scale Trends Genet. 15 1999 65 69
34. P. Mendes, and D. Kell Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation Bioinformatics 14 1998 869 883
35. C.G. Moles, P. Mendes, and R.B. Julio Parameter estimation in biochemical pathways: a comparison of global optimization methods Genome Res. 13 2003 2467 2474
36. T.C. Ni, and M.A. Savageau Model assessment and refinement using strategies from biochemical systems theory: application to metabolism in human red blood cells J. Theor. Biol. 179 1996 329 368
37. L.J. Park, C.H. Park, C. Park, and T. Lee Application of genetic algorithms to parameter estimation of bioprocesses Med. Biol. Eng. Comput. 35 1997 47 49
38. J. Pinchuk, W.A. Brown, S.M. Hughes, and D.G. Cooper Modeling of biological process using self-cycling fermentation and genetic algorithm Biotechnol. Bioeng. 67 2000 19 24
39. M. Rizzi, M. Baltes, U. Theobald, and M. Reuss In vivo analysis of metabolic dynamics in Saccharomyces cervisiae II. Mathematical model Biotechnol. Bioeng. 55 1997 592 608
40. F. Rodriguez-Acosta, C.M. Regalado, and N.V. Torres Nonlinear optimization of biotechnological processes by stochastic algorithms: application to the maximization of the production rate of ethanol, glycerol and carbohydrates by Saccharomyces cerevisiae J. Biotechnol. 68 1999 15 28
41. B.J. Ross, F. Fueten, and Y. Yashkir Automatic mineral identification using genetic programming Mach. Vision Appl. 13 2001 61 69
42. C. Ryan, and M. Keijzer An analysis of diversity of constants of genetic programming Proceedings of the European conference of genetic programming 2003 404 413
43. E. Sakamoto, and H. Iba Inferring a system of differential equations for a gene regulatory network by using genetic programming Proceedings of the Congress of Evolutionary Computation 2001 720 726
44. M.A. Savageau Reconstructionist molecular biology New Biol. 3 1991 190 197
45. M. Sebag, M. Schoenauer, and C. Ravise Inductive learning of mutation step-size in evolutionalry parameter optimization Proceedings of the Conference of Evolutionary Programming 1997 247 261
46. I. Segel Enzyme Kinetics: Behavior and Analysis of Rapid Equilibrium and Steady State Enzyme Systems 1975 John Wiley & Sons New York
47. G.G. Szpiro A search for hidden relationships: data mining with genetic algorithms Comput. Econ. 10 1997 267 277
48. A. Topchy, and W. Punch Faster genetic programming based on local gradient search of numeric leaf values Proceedings of the Genetic and Evolutionary Computation Conference 2001 Morgan Kaufmann San Francisco 155 162
49. T.E. Tuner, S. Schnell, and K. Burrage Stochastic approaches for modeling in vivo reactions Comput. Biol. Chem. 28 2004 165 178
50. B.E. Wright, and K.R. Albe Carbohydrate metabolism in Dictyostelium discoideum I. Model construction J. Theor. Biol. 169 1994 231 241
51. Z.R. Yang, R. Thomson, T.C. Hodgman, J. Dry, A.K. Doyle, A. Narayanan, and X. Wu Searching for discrimination rules in protease proteolytic cleavage activity using genetic programming with a min-max scoring function Biosystems 72 2003 159 176
52. B.T. Zhang, and H. Muehlenbein Balancing accuracy and parsimony in genetic programming Evolut. Comput. 3 1995 17 38