Computing the stochastic dynamics of phosphorylation networks

Journal of Computational Biology

Volumn 17, Issue 2, 2010, Pages 189-199

  Steijaert, M N ^a   Van Den Brink, J H K ^a   Liekens, A M L ^b   Hilbers, P A J ^a   Ten Eikelder, H M M ^a  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

Biochemical networks; Databases; Functional genomics; Genomics; Literature datamining; Stochastic processes.

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENE REGULATORY NETWORK; HUMAN; PHOSPHORYLATION; SIGNAL TRANSDUCTION; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; COMPUTER SIMULATION; GENE REGULATORY NETWORKS; HUMANS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PHOSPHORYLATION; SIGNAL TRANSDUCTION; STOCHASTIC PROCESSES;

EID: 77249133102     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2009.0059     Document Type: Article

References (16)

1. Cohen, P. 2000. The regulation of protein function by multisite phosphorylation-a 25 year update. Trends Biochem. Sci. 25, 596-601.
2. Ghaemmaghami, S., Huh, W.-K., Bower, K., et al. 2003. Global analysis of protein expression in yeast. Nature 425, 737-741.
3. Gillespie, D.T. 1976. A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys. 22, 403-434.
4. Gillespie, D.T. 2007. Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58, 35-55.
5. Goldbeter, A., and Koshland, D.E. 1981. An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl. Acad. Sci. U.S.A. 78, 6840-6844.
6. Kholodenko, B.N. 2000. Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades. FEBS J. 267, 1583.
7. Kuczyński, J., and Woźniakowski, H. 1992. Estimating the largest eigenvalue by the power and lanczos algorithms with a random start. SIAM J. Matrix Anal. Appl. 13, 1094-1122.
8. Mann, M., and Jensen, O.N. 2003. Proteomic analysis of post-translational modifications. Nat. Biotechnol. 21, 255-261.
9. McQuarrie, D.A. 1967. Stochastic approach to chemical kinetics. J. Appl. Probabil. 4, 413-478.
10. Mishra, G.R., Suresh, M., Kumaran, K., et al. 2006. Human protein reference database-2006 update. Nucleic Acids Res. 34, D411-D414.
11. Moler, C., and Van Loon, C. 2003. Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later. SIAM Rev. 45, 3-49.
12. Munsky, B., and Khammash, M. 2006. The finite state projection algorithm for the solution of the chemical master equation. J. Chem. Phys. 124, 044104.
13. Peri, S., Navarro, J., Amanchy, R., et al. 2003. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res. 13, 2363-2371.
14. Steijaert, M.N., Liekens, A.M.L., Bosnacki, D., et al. 2010. Comparison of deterministic and stochastic models of single variable reaction systems (submitted).
15. Van Kampen, N.G. 1992. Stochastic Processes in Chemistry and Physics. North-Holland, Amsterdam.
16. Ventura, A.C., Sepulchre, J.A., and Merajver, S.D. 2008. A hidden feedback in signaling cascades is revealed. PLoS Comput. Biol. 4, e1000041.