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Boolean models of regulatory networks are assumed to be tolerant to perturbations. That qualitatively implies that each function can only depend on a few nodes. Biologically motivated constraints further show that functions found in Boolean regulatory networks belong to certain classes of functions, for example, the unate functions. It turns out that these classes have specific properties in the Fourier...
Ensembles of Boolean networks using linear random threshold functions with memory are considered. Such ensembles have been studied previously by Szejka et al.. They obtained analytical results for the order parameter which can be used to predict the expected behavior of a network randomly drawn from the ensemble. Using numerical simulations of randomly drawn networks, Szejka et al. found marked deviations...
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