Random Boolean Networks

Complex systems theory deals with dynamical systems containing a very large number of variables. The resulting dynamical behavior can be arbitrary complex and sophisticated. It is therefore important to have well controlled benchmarks, dynamical systems which can be investigated and understood in a controlled way for large numbers of variables. Networks of interacting binary variables, i.e. boolean networks, constitute such canonical complex dynamical systems. They allow the formulation and investigation of important concepts, among others regarding information retention and loss and the occurrence of phase transition in the resulting dynamical states. Boolean networks are recognized to be the starting points for the modeling of gene expression and protein regulation networks; the fundamental networks at the basis of life.