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Information Processing and Biological Systems pp 113–151Cite as

Boolean Threshold Networks: Virtues and Limitations for Biological Modeling

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 11))

Abstract

Boolean threshold networks have recently been proposed as useful tools to model the dynamics of genetic regulatory networks, and have been successfully applied to describe the cell cycles of S. cerevisiae and S. pombe. Threshold networks assume that gene regulation processes are additive. This, however, contrasts with the mechanism proposed by S. Kauffman in which each of the logic functions must be carefully constructed to accurately take into account the combinatorial nature of gene regulation. While Kauffman Boolean networks have been extensively studied and proved to have the necessary properties required for modeling the fundamental characteristics of genetic regulatory networks, not much is known about the essential properties of threshold networks. Here we study the dynamical properties of these networks with different connectivities, activator-repressor proportions, activator-repressor strengths and different thresholds. Special attention is paid to the way in which the threshold value affects the dynamical regime in which the network operates and the structure of the attractor landscape. We find that only for a very restricted set of parameters, these networks show dynamical properties consistent with what is observed in biological systems. The virtues of these properties and the possible problems related with the restrictions are discussed and related to earlier work that uses these kind of models.

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Authors and Affiliations

  1. Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Colonia Chamilpa, Cuernavaca, Morelos, México, Código Postal 62210

    Jorge G. T. Zañudo, Maximino Aldana & Gustavo Martínez-Mekler

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  1. Jorge G. T. Zañudo
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  2. Maximino Aldana
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  3. Gustavo Martínez-Mekler
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Editors and Affiliations

  1. Department of Signal Processing , Tampere University of Technology, POB 553, 33101, Tampere, Finland

    Samuli Niiranen  & Andre Ribeiro  & 

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Zañudo, J.G.T., Aldana, M., Martínez-Mekler, G. (2011). Boolean Threshold Networks: Virtues and Limitations for Biological Modeling. In: Niiranen, S., Ribeiro, A. (eds) Information Processing and Biological Systems. Intelligent Systems Reference Library, vol 11. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19621-8_6

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  • DOI: https://doi.org/10.1007/978-3-642-19621-8_6

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  • Print ISBN: 978-3-642-19620-1

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