Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

ABSTRACT: This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) repres

SUBMITTER: Mdluli T 

PROVIDER: S-EPMC4574939 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature