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Stochastic analysis of autoregulatory gene expression dynamics

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  • T. Ochiai
  • J. C. Nacher

Abstract

In this work, the autoregulatory genetic module is investigated by using stochastic theory. We show here that the stochastic effect of the second order perturbation theory further reduces the fluctuation size of the gene expression level more than what is expected in deterministic methods. Furthermore, dynamical aspects of the system were investigated. In particular, we estimated the time needed to reach the equilibrium state.

Suggested Citation

  • T. Ochiai & J. C. Nacher, 2007. "Stochastic analysis of autoregulatory gene expression dynamics," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 14(4), pages 377-388, November.
    • Handle: RePEc:taf:nmcmxx:v:14:y:2007:i:4:p:377-388
    DOI: 10.1080/13873950801972186
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    References listed on IDEAS

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    1. Leland H. Hartwell & John J. Hopfield & Stanislas Leibler & Andrew W. Murray, 1999. "From molecular to modular cell biology," Nature, Nature, vol. 402(6761), pages 47-52, December.
    2. Michael B. Elowitz & Stanislas Leibler, 2000. "A synthetic oscillatory network of transcriptional regulators," Nature, Nature, vol. 403(6767), pages 335-338, January.
    3. Timothy S. Gardner & Charles R. Cantor & James J. Collins, 2000. "Construction of a genetic toggle switch in Escherichia coli," Nature, Nature, vol. 403(6767), pages 339-342, January.
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