Control in a family of Boolean networks

Intervention in a gene regulatory network is used to avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied in the framework of a probabilistic Boolean network (PBN), which is obtained by joining several Boolean networks (BN) using a probabilistic structure. In this work we treat a case in which we lack this governing probability structure for Boolean network selection, so we simply have a family of Boolean networks, where these networks possess a common attractor structure matching the data states, which are assumed to arise from sampling the steady state of the real biological network.