Networks of Cellular Information Processing: Digital Description and Simulation

The representation of gene regulation on a large-scale needs new tools and models, since interconnected networks of signal transduction rather than linear cascades of events are involved in cellular perception. The Boolean language represents a convenient way to describe such a complexity. It allows a simple representation of experimental data generated through classical genetic approaches as well as microarray analyses. In addition, it provides the possibility of computer simulation, and unlimited qualitative and quantitative data processing, that may in turn ease the identification of new signaling elements and novel modes of gene regulation. This articlepresents the properties of a Boolean representation, with digital simulations exemplified in the case of light and pathogen signal perception in plants. The general structure of cellular perception is discussed, and the results of the logical interpretation of signaling are presented in relation with space- and time-related stimuli.