Discrete-time models for gene transcriptional regulation networks

The recent finding of functional motifs (by Uri Alon and co-workers) in gene regulatory networks has provided an important interpretative tool for systems biology. Despite the available models are made of continuous-time ordinary differential equations, the experimental data needed to validate such motifs in living cells are inherently discrete in time. Moreover, the technology is currently very expensive, so that an accurate choice of a limited number of samples is mandatory. In this paper we investigate the dynamical properties of network motifs under sampling and provide simple rules for choosing the appropriate sampling rate which preserves peculiar dynamical features for the most common network motifs.