Application of Supervisory Control Theory to Guide Cellular Dynamics

In this paper we propose a theoretical framework, based on the Supervisory Control Theory, to guide the dynamics of genetic regulatory networks. The system to be controlled is abstracted by discrete-event models and the devised supervisor is assumed to be realized as a biological network, that is, it acts autonomously inside the cellular environment. The ideas presented in this paper may be extended to the more general case, where the biological plant encompasses also signaling and metabolic events. The formal synthesis of supervisors to control the behavior of cellular networks has several applications, in fields that range from the optimization of metabolites production to the treatment of diseases, such as cancer.