Optimality in the control of gene regulatory networks

Controlling the behavior of intracellular networks has many important applications in Biotechnology and Medicine. In a previous work, we showed how the ideas from Supervisory Control Theory could be used to solve the state attraction problem applied to biological cells, i.e. guiding a cell from an initial state to some target state. The devised supervisor is then implemented by means of synthetic genes that are inserted in the cell. In this paper, we borrow ideas from Optimal Supervisory Control Theory to obtain supervisors that minimize an important metric associated with the problem of controlling the behavior of intracellular networks, namely, the minimization of the energy consumed for protein synthesis along the path from the initial to the target state.