Modelling gene expression using stochastic simulation

  • Lars Kuepfer
  • Uwe Sauer
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 39)


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.


Stochastic Simulation Stochastic Simulation Algorithm Chemical Master Equation Otic Cell Deterministic Integration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [BO86]
    Bailey, J.E., Ollis, D.F.: Biochemical Engineering Fundamentals. McGraw-Hill (1986)Google Scholar
  2. [VK83]
    Kampen, van N.G.: Stochastic Processes in Physics and Chemistry. North-Holland Publishing Co., Amsterdam (1983)Google Scholar
  3. [ET88]
    Erdi, P., Toth, J., Mathematical Models of chemical reactions. Princeton University Press, Princeton (1988)Google Scholar
  4. [EL01]
    Elf, J., Lötstedt, P., Sjöberg, P.: Problems of high dimensions in molecular biology. In: Proceedings of the 17th GAMM-Seminar Leipzig 20011–10 (2001)Google Scholar
  5. [GD77]
    Gillespie, D.T., Exact Stochastic Simulation of Coupled Chemical Reactions. J. Phys. Chem.81, 2340ff (1977)Google Scholar
  6. [MC67]
    McQuarrie, D.A., Stochastic Approach to Chemical Kinetics. J. Appl. Prob.4413–478 (1967)MathSciNetzbMATHCrossRefGoogle Scholar
  7. [JB91]
    Bailey, J.E., Towards a science of metabolic engineering. Science2521668–1674 (1991)CrossRefGoogle Scholar
  8. [RC03]
    Rathinam, M., Cao, Y., Petzold, L., Gillespie, D., Stiffness in Stochastic Chemically Reacting Systems: The Implicit Tau-Leaping MethodJ. Chem. Phys., submittedGoogle Scholar
  9. [SBM03]
    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)CrossRefGoogle Scholar
  10. [VK99]
    Varner J., Ramkrishna D., Mathematical models of metabolic pathways. Curr. Opin. Biotechnol.10(2)146–50 (1999)CrossRefGoogle Scholar
  11. [JB93]
    Bailey J.E., Host-vector interactions in Escherichia coli. Adv. B iochem. Eng. Biotechnol.4829–52 (1993)Google Scholar
  12. [FE99]
    Ferrell, J.E.,Building a cellular switch: more lessons from a good egg. Bioessays. 21(10)866–70 (1999)Google Scholar
  13. [CO02]
    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)CrossRefGoogle Scholar
  14. [GS02]
    Isralewitz B., Gao M., Schulten K., Steered molecular dynamics and mechanical functions of proteins. Curr. Opin. Struct. Biol.11(2)224–30 (2001)CrossRefGoogle Scholar
  15. [KE01]
    Kepler T.B., Elston T.C., Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations. Biophys J.81(6)3116–36 (2001)CrossRefGoogle Scholar
  16. [GG02]
    Gonze D., Halloy J., Goldbeter A., Stochastic versus deterministic models for circadian rhythms. J. Biol. Phys.28637–53 (2002)CrossRefGoogle Scholar
  17. [SC03]
    Selinger D.W., Wright M.A., Church G.M., On the complete determination of biological systems. Trends Biotechnol.21(6)251–4 (2003)CrossRefGoogle Scholar
  18. [SH03]
    Stark J, Callard R, Hubank M., From the top down: towards a predictive biology of signalling networks. Trends Biotechnol.21(7)290–3 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Lars Kuepfer
    • 1
  • Uwe Sauer
  1. 1.Institute of BiotechnologyETH ZürichZürichSwitzerland

Personalised recommendations