title: Optimal Design of Non-equilibrium Experiments for Genetic Network Interrogation.
abstract: Many experimental systems in biology, especially synthetic gene networks, are amenable to perturbations that are controlled by the experimenter. We developed an optimal design algorithm that calculates optimal observation times in conjunction with optimal experimental perturbations in order to maximize the amount of information gained from longitudinal data derived from such experiments. We applied the algorithm to a validated model of a synthetic Brome Mosaic Virus (BMV) gene network and found that optimizing experimental perturbations may substantially decrease uncertainty in estimating BMV model parameters.
authors.affiliation: Department of Mathematics, Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC.
authors.forename: Kaska
authors.initials: K
authors.lastname: Adoteye
authors.affiliation: Department of Mathematics, Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC.
authors.forename: H T
authors.initials: HT
authors.lastname: Banks
authors.affiliation: Department of Mathematics, Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC.
authors.forename: Kevin B
authors.initials: KB
authors.lastname: Flores
keywords: Optimal experimental design; brome mosaic virus; genetic networks.; inverse problem; synthetic biology; uncertainty analysis