Title: Robust measurement selection for biochemical pathway experimental design

Authors: Martin Brown, Fei He, Lam Fat Yeung

Addresses: Control Systems Centre, School of Electrical and Electronic Engineering, The University of Manchester, M60 1QD, Manchester, UK. ' Control Systems Centre, School of Electrical and Electronic Engineering, The University of Manchester, M60 1QD, Manchester, UK; Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR, PR China. ' Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR, PR China

Abstract: 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.

Keywords: systems biology; experimental design; sensitivity analysis; regularisation; Taguchi methods; biochemical signal pathways; pathway modelling; parameter identification; bioinformatics; observer selection; parametric uncertainties; optimal design; robust design.

DOI: 10.1504/IJBRA.2008.021176

International Journal of Bioinformatics Research and Applications, 2008 Vol.4 No.4, pp.400 - 416

Published online: 08 Nov 2008 *

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