Modeling intrinsic noise in random Boolean networks

Noise has crucial effects on biological processes, chemical reactions, and various chaotic systems. This study explores the dynamical properties of noise in random Boolean networks, in which the stochasticity may cause significant deviations from deterministic descriptions. Such noise is intrinsic and results from the discrete dynamics of finite populations. By using methods from statistical physics and nonlinear dynamics, this study illustrates the dynamical characteristics of the inherent noise. Furthermore, a modified mean-field model is formulated to mimic the stochastic dynamics revealed by the discrete systems. The proposed idea of modeling intrinsic noise can be potentially applied to other discrete systems belonging to the category of random Boolean networks.