Reduction mappings and control policies for intervention in Boolean Networks

Finding the control policies for intervention for large PBNs is a serious computational challenge. We study the effects of reduction mappings on the policy design. Our results suggest that for a specific class of network models, one can use the control policy designed on the reduced net work to approximate the control policy for the original model. The approximation fails only for intervention policies where the cost of applying control is small.