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Italian Workshop on Artificial Life and Evolutionary Computation

WIVACE 2017: Artificial Life and Evolutionary Computation pp 88–103Cite as

Computing Hierarchical Transition Graphs of Asynchronous Genetic Regulatory Networks

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

Abstract

In the field of theoretical biology the study of the dynamics of the so-called gene regulatory networks is useful to follow the relationship between the expression of a gene and its dynamic regulatory effect on the cell fate. To date, most of the models developed for this purpose, applies the synchronous update schedule while reality is far from being so. On the other hand, the more realistic asynchronous update requires to compute all possible updates at each single instant, thus bearing a much greater computational load.

In the present work, we describe a novel method that addresses the problem of efficiently exploring the dynamics of a gene regulatory network with the asynchronous update.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Physics, Roma Tre University, Rome, Italy

    Marco Pedicini

  2. CNR - Institute for Applied Computing “M. Picone”, Rome, Italy

    Maria Concetta Palumbo & Filippo Castiglione

Authors
  1. Marco Pedicini
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  2. Maria Concetta Palumbo
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  3. Filippo Castiglione
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Corresponding author

Correspondence to Marco Pedicini .

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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Pedicini, M., Palumbo, M.C., Castiglione, F. (2018). Computing Hierarchical Transition Graphs of Asynchronous Genetic Regulatory Networks. 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_7

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  • DOI: https://doi.org/10.1007/978-3-319-78658-2_7

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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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