S-system parameter estimation for noisy metabolic profiles using Newton-flow analysis

IET Systems Biology

Volumn 1, Issue 3, 2007, Pages 174-180

  Kutalik, Z ^a   Tucker, W ^b   Moulton, V ^c  

^a UNIVERSITY OF LAUSANNE   (Switzerland)

^b UPPSALA UNIVERSITY   (Sweden)

^c UNIVERSITY OF EAST ANGLIA   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOCHEMISTRY; MATHEMATICAL MODELS; NEWTONIAN FLOW; ORDINARY DIFFERENTIAL EQUATIONS; PARAMETER ESTIMATION; TOPOLOGY;

NOISY METABOLIC PROFILES; TIME-COURSE PROFILES;

METABOLISM;

ARTICLE; BIOINFORMATICS; CELL METABOLISM; FLOW MEASUREMENT; KERNEL METHOD; MATHEMATICAL COMPUTING; SAMPLING ERROR; SIGNAL NOISE RATIO; SYSTEM ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PROTEOME; SIGNAL TRANSDUCTION; STOCHASTIC PROCESSES;

EID: 34249732527     PISSN: 17518849     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-syb:20060064     Document Type: Article

References (25)

1. Almeida, J.S., and Voit, E.O.: 'Natural-network-based parameter estimation in S-system models of biological networks', Genome Inform., 2003, 14, (1), p. 114-123
2. Cho, K.-H., and Wolkenhauer, O.: 'Analysis and modeling of signal transduction pathways in systems biology', Biochem. Soc. Trans., 2003, 31, (6), p. 1503-1509
3. Kutalik, Z., Cho, K.-H., and Wolkenhauer, O.: 'Optimal sampling time selection for parameter estimation in dynamic pathway modeling', Biosystems, 2004, 75, (1-3), p. 43-55
4. Wolkenhauer, O., Ullah, M., Wellstead, P., and Cho, K.-H.: 'The dynamic systems approach to control and regulation of intracellular networks', FEBS Letters, 2005, 579, (8), p. 1846-1853
5. Voit, E.O.: 'Computational analysis of biochemical systems', (Cambridge University Press 2000)
6. Seatzu, C.: 'A fitting based method for parameter estimation in S-systems', Dynam. Sys. Appl., 2000, 9, (1), p. 77-98
7. Voit, E.O., and Almeida, J.: 'Decoupling dynamical systems for pathway identification from metabolic profiles', Bioinformatics, 2004, 20, (11), p. 1670-1681
8. Kikuchi, S., Tominaga, D., Arita, M., Takahashi, K., and Tomita, M.: 'Dynamic modeling of genetic networks using genetic algorithm and S-system', Bioinformatics, 2003, 19, (5), p. 643-650
9. Kimura, S., Ide, K., Kashihara, A., Kano, M., Hatakeyama, M., Masui, R., Nakagawa, N., Yokoyama, S., Kuramitsu, S., and Konagaya, A.: 'Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm', Bioinformatics, 2005, 21, (7), p. 1154-1163
10. Ko, C.L., Wang, F.S., Chao, Y.P., and Chen, T.W.: 'S-system approach to modeling recombinant Escherichia coli growth by hybrid differential evolution with data collocation', Biochem. Eng. J., 2006, 28, (1), p. 10-16 0300-9467
11. Polisetty, P.K., Voit, E.O., and Gatzke, E.P.: 'Identification of metabolic system parameters using global optimization methods', Theor. Biol. Med. Model, 2006, 3, p. 4
12. Chen, B.S., and Wang, Y.C.: 'On the attenuation and amplification of molecular noice in genetic regulatory networks', BMC Bioinform., 2006, 7, p. 52
13. Schilling, M., Maiwald, T., Bohl, S., Kollmann, M., Kreutz, C., Timmer, J., and Klingmuüller, U.: 'Quantitative data generation for systems biology-the impact of randomisation, calibrators and normalisers', IEE Systems Biol., 2005, 152, (4), p. 193-200
14. Moles, C.G., Mendes, P., and Banga, J.R.: 'Parameter estimation in biochemical pathways: A comparison of global optimization methods', Genome. Res., 2003, 13, (11), p. 2467-2474
15. Gonzalez, O.R., Küper, C., Jung, K., Naval, P.C., and Mendoza, E.: 'Parameter estimation using simulated annealing for S-system models of biochemical networks', Bioinformatics, 2007, 23, (4), p. 480-486
16. Tsai, K.Y., and Wang, F.S.: 'Evolutionary optimization with data collocation for reverse engineering of biological networks', Bioinformatics, 2005, 21, (7), p. 1180-1188
17. Tucker, W., and Moulton, V.: 'Parameter reconstruction for biochemical networks using interval analysis', Reliable Computing, 2006, 12, (5), p. 1-14
18. Coleman, T.F., and Li, Y.: 'An interior, trust region approach for nonlinear minimization subject to bounds', SIAM J. Optimiz., 1996, 6, (2), p. 418-445 10.1137/0806023
19. Dedieu, J.-B., and Shub, M.: 'Newton flow and interior point methods in linear progrfamming', Internat. J. Bifur. Chaos Appl. Sci. Engrg., 2005, 15, (3), p. 827-840
20. Maki, Y., Tominaga, D., Okamoto, M., Watanabe, S., and Eguchi, Y.: 'Development of a system for the inference of large scale genetic networks', Proc. Pac. Symp., 2001, 6, p. 446-458
21. Tucker, W., Kutalik, Z., and Moulton, V.: 'Estimating parameters for generalized mass action models using constraint propagation', Math. Biosci., 2007, 23, p. 480-486 2007, In press 0025-5564
22. Marino, S., and Voit, E.O.: 'An automated procedure for the extraction of metabolic network information from time series data', J. Bioinf. Comp. Biol., 2006, 4, (3), p. 665-691
23. Nikol'skii, S.M.: 'Encyclopaedia of mathematics', (Springer-Verlag 2002)
24. Hauser, R., and Nedic, J.: 'The continuous Newton-Raphson method can look ahead', SIAM J. Optimiz., 2005, 15, (3), p. 915-925
25. Janovský, V., and Seige, V.: 'Qualitative analysis of Newton's flow', SIAM J. Num. Anal., 1996, 33, (5), p. 2068-2097