Abstract
Deterministic simulation of biological processes represents only a loose description of the actual intracellular mechanisms due to the small number of many molecular species involved in the regulatory circuits. Mesoscopic modelling that considers the systemic key species as integer numbers on a statistical basis was used in the present case study to solve a two gene sample problem in a eucaryotic cell. The results obtained with Gillespie’s stochastic simulation algorithm were compared to the deterministic integration.
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References
Bailey, J.E., Ollis, D.F.: Biochemical Engineering Fundamentals. McGraw-Hill (1986)
Kampen, van N.G.: Stochastic Processes in Physics and Chemistry. North-Holland Publishing Co., Amsterdam (1983)
Erdi, P., Toth, J., Mathematical Models of chemical reactions. Princeton University Press, Princeton (1988)
Elf, J., Lötstedt, P., Sjöberg, P.: Problems of high dimensions in molecular biology. In: Proceedings of the 17th GAMM-Seminar Leipzig 20011–10 (2001)
Gillespie, D.T., Exact Stochastic Simulation of Coupled Chemical Reactions. J. Phys. Chem.81, 2340ff (1977)
McQuarrie, D.A., Stochastic Approach to Chemical Kinetics. J. Appl. Prob.4413–478 (1967)
Bailey, J.E., Towards a science of metabolic engineering. Science2521668–1674 (1991)
Rathinam, M., Cao, Y., Petzold, L., Gillespie, D., Stiffness in Stochastic Chemically Reacting Systems: The Implicit Tau-Leaping MethodJ. Chem. Phys., submitted
Hucka et. al, The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinf.19(4)524–31 (2003)
Varner J., Ramkrishna D., Mathematical models of metabolic pathways. Curr. Opin. Biotechnol.10(2)146–50 (1999)
Bailey J.E., Host-vector interactions in Escherichia coli. Adv. B iochem. Eng. Biotechnol.4829–52 (1993)
Ferrell, J.E.,Building a cellular switch: more lessons from a good egg. Bioessays. 21(10)866–70 (1999)
Cooper T.G., Transmitting the signal of excess nitrogen in Saccharomyces cerevisiae from the Tor proteins to the GATA factors: connecting the dots. FEMS Microbiol. Rev.26(3)223–38 (2002)
Isralewitz B., Gao M., Schulten K., Steered molecular dynamics and mechanical functions of proteins. Curr. Opin. Struct. Biol.11(2)224–30 (2001)
Kepler T.B., Elston T.C., Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations. Biophys J.81(6)3116–36 (2001)
Gonze D., Halloy J., Goldbeter A., Stochastic versus deterministic models for circadian rhythms. J. Biol. Phys.28637–53 (2002)
Selinger D.W., Wright M.A., Church G.M., On the complete determination of biological systems. Trends Biotechnol.21(6)251–4 (2003)
Stark J, Callard R, Hubank M., From the top down: towards a predictive biology of signalling networks. Trends Biotechnol.21(7)290–3 (2003)
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Kuepfer, L., Sauer, U. (2004). Modelling gene expression using stochastic simulation. In: Attinger, S., Koumoutsakos, P. (eds) Multiscale Modelling and Simulation. Lecture Notes in Computational Science and Engineering, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18756-8_20
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DOI: https://doi.org/10.1007/978-3-642-18756-8_20
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