The inference of genome-wide regulatory networks in cells from high-throughput data sets has revealed a diverse picture of only partly overlapping descriptions. Nevertheless, several conclusions of the large-scale properties in the organization of these networks are possible. For example, the presence of hubs, a modular structure and certain motifs are recurrent phenomena.
Several authors have recently claimed cell systems to be stable against perturbations and random errors, but still able to rapidly switch between different states from specific stimuli. Since inferred genome-wide systems need to be extremely simple to avoid overfitting, these two features are hard to attain simultaneously in a mathematical model. Here we review and discuss possible measures of how system stability and flexibility may be manifested and measured for linear ODE models. Furthermore, we review how different network properties contribute to these systems level properties. It turns out that the presence of repressed hubs, together with other phenomena of topological nature such as motifs and modules, contributes to the overall stability and/or flexibility of the system.