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On Computing Structural and Behavioral Complexities of Threshold Boolean Networks

Application to Biological Networks

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Abstract

Various threshold Boolean networks (TBNs), a formalism used to model different types of biological networks (genes notably), can produce similar dynamics, i.e. share same behaviors. Among them, some are complex (according to Kolmogorov complexity), others not. By computing both structural and behavioral complexities, we show that most TBNs are structurally complex, even those having simple behaviors. For this purpose, we developed a new method to compute the structural complexity of a TBN based on estimates of the sizes of equivalence classes of the threshold Boolean functions composing the TBN.

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Notes

  1. The \(^*\) operator is the usual Kleene star, denoting any number of repetitions of a substring.

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Correspondence to Nicolas Glade.

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Christen, U., Ivanov, S., Segretain, R. et al. On Computing Structural and Behavioral Complexities of Threshold Boolean Networks. Acta Biotheor 68, 119–138 (2020). https://doi.org/10.1007/s10441-019-09358-8

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