Robust measurement selection for biochemical pathway experimental design

Martin Brown, Fei He, Lam Fat Yeung

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)400-416
Number of pages17
JournalInternational Journal of Bioinformatics Research and Applications
Issue number4
Publication statusPublished - 8 Nov 2008
Externally publishedYes


  • Experimental design
  • Regularisation
  • Sensitivity analysis
  • Systems biology
  • Taguchi design

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management


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