title: Robustness of inverse perturbation for discrete event control.
abstract: We study the robustness of the inverse perturbation solution in discrete-time systems modeled by homogeneous Markov chains. We cast the optimal inverse perturbation control as a strictly convex optimization problem, which admits a unique global solution. We show that the optimal inverse perturbation control is robust to estimation errors in the original network. The derived results are applied to the Human melanoma gene regulatory network, where the aim is to force the network to converge to a desired steady-state distribution of gene regulation.
authors.affiliation: Dept of Systems Engineering, University of Arkansas at Little Rock, USA.
authors.forename: Nidhal
authors.initials: N
authors.lastname: Bouaynaya
authors.forename: Roman
authors.initials: R
authors.lastname: Shterenberg
authors.forename: Dan
authors.initials: D
authors.lastname: Schonfeld
mesh_terms: D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008390:Markov Chains; D008545:Melanoma / Q000378:metabolism*; D008954:Models, Biological; D015233:Models, Statistical; D009363:Neoplasm Proteins / Q000378:metabolism*
chemical_list: D009363:Neoplasm Proteins