Choices of regulatory logic class modulate the dynamical regime in random Boolean networks

Priyotosh Sil, Suchetana Mitra, Olivier C. Martin and Areejit Samal

Chaos, Solitons & Fractals, 2025, vol. 195, issue C

Abstract: Random Boolean networks (RBNs) have been widely explored as model complex systems and as simplified gene regulatory networks. Stability (order) and instability (chaos), essential characteristics of any dynamical system, have naturally been a central focus in RBN research. Stability has been assessed using measures like damage spreading and attractor properties (e.g. number, length and basin size). Although network topology is known to influence network dynamics, Boolean functions (BFs) assigned to each node play an equally crucial role. In this work, we systematically examine the influence of five different classes of BFs on the dynamics of RBNs. By employing various dynamical stability measures, we show that compared to random BFs, biologically meaningful BFs consistently drive the dynamics towards the ordered regime, regardless of network size, connectivity, and degree distributions. Moreover, the values of the stability measures change differently across BF classes as network connectivity or size increases: random BFs typically push the dynamics towards a more chaotic regime whereas biologically meaningful BFs show very minimal fluctuations for most stability measures. These findings emphasize the advantage of restricting to biologically meaningful classes in the reconstruction and modeling of biological systems within Boolean framework.

Keywords: Gene regulatory networks; Random Boolean networks; Update rules; Dynamics; Stability; Damage spreading (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:195:y:2025:i:c:s0960077925002449

DOI: 10.1016/j.chaos.2025.116231

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