Model simplification of signal transduction pathway networks via a hybrid inference strategy

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 17, Issue 1 PART 1, 2008, Pages

  Jia, Jianfang ^a   Yue, Hong ^b  

^a NORTH UNIVERSITY OF CHINA   (China)

^b UNIVERSITY OF STRATHCLYDE   (United Kingdom)

Author keywords

Cellular, metabolic, cardiovascular, neurosystems; Model formulation, experiment design

Indexed keywords

AUTOMATION; PROCESS CONTROL; SENSITIVITY ANALYSIS; SIGNAL TRANSDUCTION;

CELLULAR NETWORK; CELLULAR, METABOLIC, CARDIOVASCULAR, NEUROSYSTEM; CELLULARS; EXPERIMENT DESIGN; HYBRID INFERENCE; MODEL FORMULATION; MODEL FORMULATION, EXPERIMENT DESIGN; MODEL SIMPLIFICATION; NEUROSYSTEMS; SIGNAL TRANSDUCTION PATHWAYS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 79961019741     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20080706-5-kr-1001.01744     Document Type: Conference Paper

References (28)

1. A.R. Asthagiri, and D.A. Lauffenburger. Bioengineering models of cell signaling. Annual Review of Biomedical Engineering, 2:31-53, 2000.
2. U.S. Bhalla. Biochemical signaling networks decode temporal patterns of synaptic input. J. Computational Neuroscience, 13:49-62, 2002.
3. R. Cheong, A. Bergmann, S.L. Werner, J. Regal, A. Hoffmann, an d A. Levchenko. Transient IkB kinase activity mediates temporal NF-kappaB dynamics in response to a wide range of tumor necrosis factor-alpha doses. J. Biological Chemistry, 281:2945-2950, 2006.
4. H. Conzelmann, J. Saez-Rodriguez, T. Sauter, E. Bullinger, F. Allgower, and E.D. Gilles. Reduction of mathematical models of signal transduction networks: simulation-based approach applied to EGF receptor signalling. IEE Proc. Systems Biology, 1:159-169, 2004.
5. H. Conzelmann, J. Saez-Rodriguez, T. Sauter, B.N. Kholodenko, and E.D. Gilles. A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks. BMC Bioinformatics, 7:34, 2006.
6. M.W. Covert, T.H. Leung, J.E. Gaston, and D. Baltimore. Achieving stability of lipopolysaccharide-induced NF-kB activation. Science, 309:1854-1857, 2005.
7. S. Dano, M.F. Madsen, H. Schmidt, and G. Cedersund. Reduction of a biochemical model with preservation of its basic dynamic properties. FEBS J., 273:4862-4877, 2006.
8. D. Degenring, C. Froemel, G. Dikta, and R. Takors. Sensitivity analysis for the reduction of complex metabolism models. J. Process Control, 14:729-745, 2004.
9. D.A. Fell. Understanding the control of metabolism. Portland Press, London, 1996.
10. R. Heinrich, and S. Schuster. The Regulation of Cellular Systems. Springer, New York, 1996.
11. A. Hoffmann, and D. Baltimore. Circuitry of nuclear factor kappaB signaling. Immunological Reviews, 210:171-186, 2006.
12. A. Hoffmann, A. Levchenko, M.L. Scott, and D. Baltimore. The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science, 298:1241-1245, 2002. (Pubitemid 35285493)
13. A.E.C. Ihekwaba, D.S. Broomhead, R.L. Grimley, N. Benson, M.R. H. White, and D.B. Kell. Sensitivity analysis of parameters controlling oscillatory signalling in the NF-kappaB pathway: the roles of IKK and IkappaBalpha. IEE Proc. Systems Biology, 1:93-103, 2004.
14. B.P. Ingalls, and H.M. Sauro. Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories. J. Theoretical Biology, 222:23-36, 2003.
15. J.F. Jia, T.Y. Liu, H. Yue and H. Wang. Robustness analysis of signaling transduction networks based on Monte-Carlo method. Computer Simulation, 24:295-299, 2007.
16. J.D. Kearns, S. Basak, S.L. Werner, C.S. Huang, and A. Hoffmann. IkappaBepsilon provides negative feedback to control NF-kappaB oscillations, signaling dynamics, and inflammatory gene expression. J. Cell Biology, 173:659-664, 2006.
17. S. Krishna, M.H. Jensen, and K. Sneppen. Minimal model of spiky oscillations in NF-kappaB signaling. PNAS, 103: 10840-10845, 2006.
18. R. Kruger, and R. Heinrich. Model reduction and analysis of robustness for the Wnt/beta-catenin signal transduction pathways. Genome Informatics, 15:138-148, 2004.
19. T. Lipniacki, P. Paszek, A.R. Brasier, B. Luxon, and M. Kimmel. Mathematical model of NF-kappaB regulatory module. J. Theoretical Biology, 228:195-215, 2004.
20. G. Liu, M.T. Swihart, and S. Neelamegham. Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling. Bioinformatics, 21:1194-1202, 2005.
21. M.R. Mauryaa, S. Katare, P.R. Patkar, A.E. Rundell, and V. Venkatasubramanian. A systematic framework for the design of reduced-order models for signal transduction pathways from a control theoretic perspective. Computers & Chemical Engineering, 30:437-452, 2006.
22. D.E. Nelson, A.E.C. Ihekwaba, M. Elliott, J.R. Johnson, C.A. Gibney, B.E. Foreman, G. Nelson, V. See, C.A. Horton, D.G. Spiller, S.W. Edwards, H.P. McDowell, J.F. Unitt, E. Sullivan, R.L. Grimley, N. Benson, D.S. Broomhead, D.B. Kell, and M.R.H. White. Oscillations in NF-kappaB signaling control the dynamics of gene expression. Science, 306:704-708, 2004. (Pubitemid 39440922)
23. S.R. Neves, and R. Iyengar. Modeling of signaling networks. Bioessays, 24:1110-1117, 2002.
24. E.L. O'Dea, D. Barken, R.Q. Peralta, K.T. Tran, S.L. Werner, J.D. Kearns, A. Levchenko, and A. Hoffmann. A homeostatic model of IkappaBmetabolism to control constitutive NF-kappaB activity. Molecular Systems Biology, 3:111, 2007.
25. S.L. Werner, D. Barken, and A. Hoffmann. Stimulus specificity of gene expression programs determined by temporal control of ikk activity. Science, 309:1857-1861, 2007.
26. M.C. Wildermuth. Metabolic control analysis: biological applications and insights. Genome Biology, 1:1031.1-1031.6, 2000.
27. H. Yue, M. Brown, J. Knowles, H. Wang, D.S. Broomhead and D.B. Kell. Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of an NF-kB signaling pathway. Molecular Biosystems, 2:640-649, 2006.
28. H. Yue, M. Brown, Y. Wang and D.B. Kell. Sensitivity analysis of an oscillatory signal transduction pathway. Proc. 2nd Foundations of Systems Biology in Engineering, Stuttgart, Germany: 99-104, 2007.