The Matlab tool for Prediction Uncertainty Analysis (PUA) integrates Profile Likelihood analysis with Bayesian sampling. Different analyses are performed sequentially to detect and avoid problems associated with the individual techniques. The PUA approach enables computation of a Posterior Predictive Distribution (PPD), which subsequently can be used for different types of analyses and experimental design.
Application: Systems Biology employs mathematical modelling of biological reaction networks by systems of nonlinear differential equations. Model parameters need to be estimated using experimental data. Given the complexity of the models in combination with the limited amount of quantitative data it is important to infer how well model parameters can be determined and how uncertainty in parameters propagates into model predictions. Model identifiability and uncertainty analysis are becoming increasingly important topics in Systems Biology.