In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost. The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks.
Shuqin Zhang, Michael K. Ng, Wai-Ki Ching, Tatsuya