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Dynamical Criticality in Gene Regulatory Networks

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  • Marco Villani
  • Luca La Rocca
  • Stuart Alan Kauffman
  • Roberto Serra

Abstract

A well-known hypothesis, with far-reaching implications, is that biological evolution should preferentially lead to states that are dynamically critical. In previous papers, we showed that a well-known model of genetic regulatory networks, namely, that of random Boolean networks, allows one to study in depth the relationship between the dynamical regime of a living being’s gene network and its response to permanent perturbations. In this paper, we analyze a huge set of new experimental data on single gene knockouts in S. cerevisiae , laying down a statistical framework to determine its dynamical regime. We find that the S. cerevisiae network appears to be slightly ordered, but close to the critical region. Since our analysis relies on dichotomizing continuous data, we carefully consider the issue of an optimal threshold choice.

Suggested Citation

  • Marco Villani & Luca La Rocca & Stuart Alan Kauffman & Roberto Serra, 2018. "Dynamical Criticality in Gene Regulatory Networks," Complexity, Hindawi, vol. 2018, pages 1-14, October.
    • Handle: RePEc:hin:complx:5980636
    DOI: 10.1155/2018/5980636
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    Cited by:

    1. Omar K. Pineda & Hyobin Kim & Carlos Gershenson, 2019. "A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks," Complexity, Hindawi, vol. 2019, pages 1-10, May.
    2. Gianluca D’Addese & Martina Casari & Roberto Serra & Marco Villani, 2021. "A Fast and Effective Method to Identify Relevant Sets of Variables in Complex Systems," Mathematics, MDPI, vol. 9(9), pages 1-27, April.

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