Robust measurement selection for biochemical pathway experimental design
by Martin Brown, Fei He, Lam Fat Yeung
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 4, No. 4, 2008

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.

Online publication date: Sat, 08-Nov-2008

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bioinformatics Research and Applications (IJBRA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com