The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable ...
Kauffman N-K (Random Boolean) networks are a generalization of cellular automata and serve as a theoretical model of gene regulation. In these networks, each node represents a gene, and each gene can ...
Amid efforts to address energy consumption in modern computing systems, one promising approach takes advantage of random networks of non-linear nanoscale junctions formed by nanoparticles as ...
Abstract: This paper considers the stabilization of random Boolean networks. We first give a survey on the semi-tensor product approach to Boolean (control) networks, which is a new technique ...
We determine stability and attractor properties of random Boolean genetic network models with canalyzing rules for a variety of architectures. For all power law, exponential, and flat in-degree ...
There are many examples of complex networks in science. It can be genetic regulation in living cells, computers on the Internet, or social and economic networks. In this context, Boolean networks ...
Despite their apparent simplicity, random Boolean networks display a rich variety of dynamical behaviors. Much work has been focused on the properties and abundance of attractors. The topologies of ...
A random Boolean network is a mathematical model used to study the dynamics of complex systems, particularly in fields such as biology and physics. It consists of a collection of binary variables ...
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