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Italian Workshop on Artificial Life and Evolutionary Computation

WIVACE 2018: Artificial Life and Evolutionary Computation pp 30–41Cite as

Self-loops Favour Diversification and Asymmetric Transitions Between Attractors in Boolean Network Models

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 900))

Abstract

The process of cell differentiation manifests properties such as non-uniform robustness and asymmetric transitions among cell types. In this paper we adopt Boolean networks to model cellular differentiation, where attractors (or set of attractors) in the network landscape epitomise cell types. Since changes in network topology and functions strongly impact attractor landscape characteristics, in this paper we study how self-loops influence diversified robustness and asymmetry of transitions. The purpose of this study is to identify the best configuration for a network owning these properties. Our results show that a moderate amount of self-loops make random Boolean networks more suitable to reproduce differentiation phenomena. This is a further evidence that self-loops play an important role in genetic regulatory networks.

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Notes

  1. 1.

    As done in [11].

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Acknowledgements

We thank the anonymous referees for useful comments and suggestions. Andrea Roli is a member of the INdAM Research group GNCS.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Alma Mater Studiorum, Università di Bologna, Campus of Cesena, via dell’Università 50, 47522, Cesena, Italy

    Michele Braccini, Sara Montagna & Andrea Roli

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

Correspondence to Michele Braccini .

Editor information

Editors and Affiliations

  1. University of Parma, Parma, Italy

    Stefano Cagnoni

  2. University of Parma, Parma, Italy

    Monica Mordonini

  3. Università degli Studi eCampus, Novedrate, Italy

    Riccardo Pecori

  4. University of Bologna, Cesena, Italy

    Andrea Roli

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

    Marco Villani

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Braccini, M., Montagna, S., Roli, A. (2019). Self-loops Favour Diversification and Asymmetric Transitions Between Attractors in Boolean Network Models. In: Cagnoni, S., Mordonini, M., Pecori, R., Roli, A., Villani, M. (eds) Artificial Life and Evolutionary Computation. WIVACE 2018. Communications in Computer and Information Science, vol 900. Springer, Cham. https://doi.org/10.1007/978-3-030-21733-4_3

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  • DOI: https://doi.org/10.1007/978-3-030-21733-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21732-7

  • Online ISBN: 978-3-030-21733-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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