Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.