Robust measurement selection for biochemical pathway experimental design

As a general lack of quantitative measurement data for pathway modelling and parameter identification process, time-series experimental design is particularly important in current systems biology research. This paper mainly investigates state measurement/observer selection problem when parametric uncertainties are considered. Based on the extension of optimal design criteria, two robust experimental design strategies are investigated, one is the regularisation-based design method, and the other is Taguchi-based design approach. By implementing to a simplified IκBα - NF - κB signalling pathway system, two design approaches are comparatively studied. When large parametric uncertainty is present, by assuming that different parametric uncertainties are identical in scale, two methods tend to provide a similar uniform design result.