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Italian Workshop on Artificial Life and Evolutionary Computation

WIVACE 2017: Artificial Life and Evolutionary Computation pp 116–128Cite as

A Comparison Between Threshold Ergodic Sets and Stochastic Simulation of Boolean Networks for Modelling Cell Differentiation

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

Abstract

Recently a cell differentiation model based on noisy random Boolean networks has been proposed. This mathematical model is able to describe in an elegant way the most relevant features of cell differentiation. Noise plays a key role in this model; the different stages of the differentiation process are emergent dynamical configurations deriving from the control of the intracellular noise level. In this work we compare two approaches to this cell differentiation framework: the first one (already present in the literature) is focused on a network analysis representing the average wandering of the system among its attractors, whereas the second (new) approach takes into consideration the dynamical stories of thousands of individual cells. Results showed that under a particular noise condition the two approaches produce comparable results. Therefore both can be used to model the cell differentiation process in an integrative and complementary manner.

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Notes

  1. 1.

    It is abstract because does not refer to a specific organism or cell type.

  2. 2.

    This hypothesis is supported by the observation that cells have a finite lifetime, which enables their dynamics to explore only a portion of the possible attractor transitions.

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Author information

Authors and Affiliations

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

    Michele Braccini & Andrea Roli

  2. Department of Physics, Informatics and Mathematics, Università di Modena e Reggio Emilia, Modena, Italy

    Marco Villani & Roberto Serra

  3. European Centre for Living Technology, Venice, Italy

    Marco Villani & Roberto Serra

Authors
  1. Michele Braccini
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  2. Andrea Roli
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  3. Marco Villani
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  4. Roberto Serra
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Corresponding author

Correspondence to Michele Braccini .

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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Braccini, M., Roli, A., Villani, M., Serra, R. (2018). A Comparison Between Threshold Ergodic Sets and Stochastic Simulation of Boolean Networks for Modelling Cell Differentiation. 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_9

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  • DOI: https://doi.org/10.1007/978-3-319-78658-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78657-5

  • Online ISBN: 978-3-319-78658-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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