Conf Proc IEEE Eng Med Biol Soc 2005;2005:2966-70
Bachelor of Tech. Programme, Nat. Univ. of Singapore.
In this paper, an approach based on Markov chains for controlling gene networks is proposed. The state of the network is represented as a probability distribution, while state transitions are considered to be probabilistic. An algorithm is proposed to determine a sequence of control actions that drives the state of a given network to within a desired state set with a prescribed minimum or maximum probability. A heuristic is proposed and shown to improve the efficiency of the proposed algorithm for a class of gene networks.