Discovery of regulatory interactions through perturbation: inference and experimental design.

摘要: We present two methods to be used interactively infer a genetic network from gene expression measurements. The predictor method determines the set of Boolean networks consistent with an observed steady-state profiles, each generated different perturbation network. chooser uses entropy-based approach propose additional experiment discriminate among hypothetical determined by predictor. These may iteratively and successively refine network: at iteration, selected is experimentally performed generate new profile, derive refined using cumulative data. Performance evaluated on simulated varying number genes interactions per gene.