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Analysing Dynamical Behavior of Cellular Networks via Stochastic Bifurcations

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  • Anna Zakharova
  • Jürgen Kurths
  • Tatyana Vadivasova
  • Aneta Koseska

Abstract

The dynamical structure of genetic networks determines the occurrence of various biological mechanisms, such as cellular differentiation. However, the question of how cellular diversity evolves in relation to the inherent stochasticity and intercellular communication remains still to be understood. Here, we define a concept of stochastic bifurcations suitable to investigate the dynamical structure of genetic networks, and show that under stochastic influence, the expression of given proteins of interest is defined via the probability distribution of the phase variable, representing one of the genes constituting the system. Moreover, we show that under changing stochastic conditions, the probabilities of expressing certain concentration values are different, leading to different functionality of the cells, and thus to differentiation of the cells in the various types.

Suggested Citation

  • Anna Zakharova & Jürgen Kurths & Tatyana Vadivasova & Aneta Koseska, 2011. "Analysing Dynamical Behavior of Cellular Networks via Stochastic Bifurcations," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-12, May.
    • Handle: RePEc:plo:pone00:0019696
    DOI: 10.1371/journal.pone.0019696
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    Cited by:

    1. Semenov, Vladimir V., 2018. "Self-oscillation excitation under condition of positive dissipation in a state-dependent potential well," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 358-364.
    2. Masoliver, Maria & Masoller, Cristina & Zakharova, Anna, 2021. "Control of coherence resonance in multiplex neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).

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