Are cells really operating at the edge of chaos? A case study of two real-life regulatory networks

Abstract

It has been suggested that the cells of living organisms are functioning in a near chaotic regime called critical, which offers a trade-off between stability and evolvability. Abstract models for regulatory networks such as Kauffman's Random Boolean Networks certainly point in that direction. In this work, we applied the essence of these models to investigate the dynamical behavior of two real-life genetic regulatory networks, deduced in two different organisms. Moreover, a novel, more biologically accurate, way individual genes respond to activation signaling is investigated. We perform numerical simulation and successfully identify contexts in which our model's response can be interpreted as critical, thus most biologically plausible. We also discover that results are comparable in both studied organisms. © 2011 Springer-Verlag.