Search Results for "inference"

We introduce optPBN, a Matlab-based toolbox for the optimization of probabilistic Boolean networks (PBN) which operates under the framework of the BN/PBN toolbox from Shmulevich et al. optPBN offers an easy generation of probabilistic Boolean networks from Boolean rule-based modeling and allows for flexible measurement data integration from multiple experiments and a subsequent integrated optimization problem generation which then can be solved with different optimizers. Thereby optPBN allows for the identification of Boolean functions in the model from a given set of candidate Boolean rules which can be applied for network inference study. In addition, it also permits the determination of selection probabilities of Boolean rules in PBNs which can be further used to determine the influence of parent nodes in biochemical interactions.