Using dynamic perturbations to identify fragilities in biochemical networks

International Journal of Robust and Nonlinear Control

Volumn 20, Issue 9, 2010, Pages 1027-1046

  Jacobsen, Elling W ^a   Trane, Camilla ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

Bifurcations; Biochemical reaction networks; Robustness

Indexed keywords

BI-STABILITY; BINARY INTERACTIONS; BIOCHEMICAL NETWORK; BIOCHEMICAL REACTION NETWORK; BIOLOGICAL FUNCTIONS; BIOLOGICAL MALFUNCTIONS; CELLULAR LEVELS; DISEASE STATE; MITOGEN ACTIVATED PROTEIN KINASE; MODELING TOOL; NETWORK EDGES; NETWORK FUNCTIONS; QUALITATIVE CHANGES; SUSTAINED OSCILLATIONS;

BIFURCATION (MATHEMATICS); BIOLOGY; PROTEINS; ROBUST CONTROL;

SIGNAL TRANSDUCTION;

EID: 77952998402     PISSN: 10498923     EISSN: 10991239     Source Type: Journal    
DOI: 10.1002/rnc.1590     Document Type: Article

References (34)

1. Kitano H. Biological robustness. Nature Reviews Genetics 2004; 5(11):826-837.
2. Stelling J, Sauer U, Szallasi Z, Doyle FJ, Doyle J. Robustness of cellular functions. Cell 2004; 118:675-685.
3. Kitano H. Towards a theory of biological robustness. Molecular Systems Biology 2007 ; 3:1-7.
4. Stelling J, Gilles ED, Doyle FJ. Robustness properties of circadian clock architectures. Proceedings of the National Academy Sciences USA 2004; 101(36):13210-13215.
5. Locke JC, Westermark PO, Kramer A, Herzel H. Global parameter search reveals design principles of the mammalian circadian clock. BMC Systems Biology 2008; 2:1-9.
6. Wagner A. Circuit topology and the evolution of robustness in two-gene circadian oscillators. Proceedings of the National Academy Sciences USA 2005; 102(33):11775-11780.
7. Chen BS, Wang YC, Wu WS, Li WH. A new measure of the robustness of biochemical networks. Bioinformatics 2005; 21(11): 2698-2705.
8. Cross FR. Two redundant oscillatory mechanisms in the yeast cell cycle. Developmental Cell 2003; 4(5):741-752.
9. Morohashi M, Winn AE, Borisuk MT, Bolouri H, Doyle J, Kitano H. Robustness as a measure of plausibility in models of biochemical networks. Journal of Theoretical Biology 2002; 216(1):19-30.
10. Wilhelm T, Behre J, Schuster S. Analysis of structural robustness of metabolic networks. Systems Biology 2004; 1(1):114-120.
11. Jacobsen EW, Cedersund G. Structural robustness of biochemical network models-with application to the oscillatory metabolism of activated neutrophils. IETSystems Biology 2008; 2(1):39-47.
12. Novak B, Tysom JJ. Design principles of biochemical oscillators. Nature Reviews Molecular Cell Biology 2008; 9:981-991.
13. Roenneberg T, Chua EJ, Bernardo R, Mendoza E. Modelling biological rhythms. Current Biology 2008; 18(17).
14. Eissing T, Allgöwer F, Bullinger E. Robustness properties of apoptosis models with respect to parameter variations and intrinsic noise. Systems Biology 2005; 152(4):221-228.
15. Ma L, Iglesias PA. Quantifying robustness of biochemical network models. BMC Bioinformatics 2002; 3:1-13.
16. Kim J, Bates DG, Postlethwaite I, Ma L, Iglesias PA. Robustness analysis of biochemical network models. Systems Biology 2006; 153:96-104.
17. Qiao L, Nachbar RB, Kevrekidis IG, Shvartsman SY. Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. PLoS Computational Biology 2007; 3(9):e184.
18. Francois P. A model for the neurospora circadian clock. Biophysical Journal 2005; 88:2369-2383.
19. Conrad ED, Tyson JJ. Modeling molecular interaction networks with nonlinear differential equations. System Modeling in Cellular Biology. MIT Press: Cambridge, MA, 2006.
20. Kell DB, Knowles JD. The role of modeling in systems biology. System Modeling in Cellular Biology. MIT Press: Cambridge, MA, 2006.
21. Guckenheimer J, Holmes P. Nonlinear Oscillations' Dynamical Systems' and Bifurcations of Vector Fields (2nd edn). Springer: New York, 1986.
22. Seydel R. Practical Bifurcation and Stability Analysis. From Equilibriumto Chaos. Springer: 1994.
23. Hinrichsen D, Pritchard AJ. Mathematical Systems Theory I. Springer: Berlin, 2005.
24. Packard A, Doyle J. The complex structured singular value. Automatica 1993; 29:71-109.
25. Braatz RP, Young PM, Doyle JC, Morari M. Saccharomyces cerevisiae. IEEE Transactions on Automatic Control 1994; 39(5): 1000-1002.
26. Doyle J, Zhou K, Glover K. Robust and Optimal Control. Prentice-Hall: Eaglewood Cliffs, NJ, 1996.
27. Danö S, Hynne F, Sörensen PG. Full-scale model of glycolysis in Saccharomyces cerevisiae. Biophysical Chemistry 2001; 92:121-163.
28. Hornberg JJ, Bruggeman FJ, Binder B, Geest CR, de Vaate AJMB, Lankelma J, Heinrich R, Westerhoff HV. Principles behind the multifarious control of signal transduction. ERK phosphorylation and kinase/phosphatase control. FEBS Journal 2005; 272(1):244-258.
29. Huang CY, Ferrell JE. Ultrasensitivity in the mitogen-activated protein kinase cascade. Proceedings of the National Academy Sciences USA 1996; 93:10078-10083.
30. Ferrell Jr JE, Machleder EM. The biochemical basis of an all-or-none cell fate switch in Xenopus oocytes. Science 1998; 280:895-898.
31. Hilioti Z, Sabbagh W, Paliwal S, Bergmann A, Goncalves MD, Bardwell L, Levchenko A. Oscillatory phosphorylation of yeast Fus3 MAP kinase controls periodic gene expression and morphogenesis. Current Biology 2008; 18(21):1700-1706.
32. Kholodenko BN. Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades. European Journal of Biochemistry 2000; 267(6):1583-1588.
33. Blüthgen N, Legewie S, Schoeberl B, Herzel H. Competing docking interactions can bring about testability in the MAPK cascade. Biophysical Journal 2007; 93:2279-2288.
34. Waldherr S, Allgower F, Jacobsen EW. Kinetic perturbations as robustness analysis tool for biochemical reaction networks. Proceedings of the 48th IEEE Conference on Decision and Control. IEEE: Shangahi, China, 2009.