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The Impact of Self-loops in Random Boolean Network Dynamics: A Simulation Analysis

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Artificial Life and Evolutionary Computation (WIVACE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 830))

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Abstract

Random Boolean Networks (RBNs) are a popular and successful model of gene regulatory networks, especially for analysing emergent properties of cell dynamics. Since completely random networks are unrealistic, some work has been done to extend the original model with structural and functional properties observed in biological networks. Among recurring motifs identified by experimental studies, auto-regulation seems to play a significant role in gene regulatory networks. In this paper we present a model of auto-regulatory mechanisms by introducing self-loops in RBNs. Experiments are performed to analyse the impact of self-loops in the RBNs asymptotic behaviour. Results show that the number of attractors increases with the amount of self-loops, while their robustness and stability decrease.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Campus of Cesena, Alma Mater Studiorum, Università di Bologna, Cesena, Italy

    Sara Montagna, Michele Braccini & Andrea Roli

Authors
  1. Sara Montagna
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  2. Michele Braccini
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  3. Andrea Roli
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Corresponding author

Correspondence to Sara Montagna .

Editor information

Editors and Affiliations

  1. Ca’ Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  2. Ca’ Foscari University of Venice, Venice, Italy

    Irene Poli

  3. University of Bologna, Cesena, Italy

    Andrea Roli

  4. University of Modena and Reggio Emilia, Modena, Italy

    Roberto Serra

  5. Ca’ Foscari University of Venice, Venice, Italy

    Debora Slanzi

  6. University of Modena and Reggio Emilia, Modena, Italy

    Marco Villani

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Montagna, S., Braccini, M., Roli, A. (2018). The Impact of Self-loops in Random Boolean Network Dynamics: A Simulation Analysis. In: Pelillo, M., Poli, I., Roli, A., Serra, R., Slanzi, D., Villani, M. (eds) Artificial Life and Evolutionary Computation. WIVACE 2017. Communications in Computer and Information Science, vol 830. Springer, Cham. https://doi.org/10.1007/978-3-319-78658-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-78658-2_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78657-5

  • Online ISBN: 978-3-319-78658-2

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