Robust measurement selection for biochemical pathway experimental design

Martin Brown, Fei He, Lam Fat Yeung

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)400-416
Number of pages17
JournalInternational Journal of Bioinformatics Research and Applications
Volume4
Issue number4
DOIs
Publication statusPublished - 8 Nov 2008
Externally publishedYes

Fingerprint

Design of experiments
Uncertainty
Research Design
Systems Biology
Time series
Identification (control systems)
Research

Keywords

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

ASJC Scopus subject areas

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

Cite this

Robust measurement selection for biochemical pathway experimental design. / Brown, Martin; He, Fei; Yeung, Lam Fat.

In: International Journal of Bioinformatics Research and Applications, Vol. 4, No. 4, 08.11.2008, p. 400-416.

Research output: Contribution to journalArticle

@article{9b1af110cd2e4ae2aa84a865eaf1e1b1,
title = "Robust measurement selection for biochemical pathway experimental design",
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 = "Experimental design, Regularisation, Sensitivity analysis, Systems biology, Taguchi design",
author = "Martin Brown and Fei He and Yeung, {Lam Fat}",
year = "2008",
month = "11",
day = "8",
doi = "10.1504/IJBRA.2008.021176",
language = "English",
volume = "4",
pages = "400--416",
journal = "International Journal of Bioinformatics Research and Applications",
issn = "1744-5485",
publisher = "Inderscience",
number = "4",

}

TY - JOUR

T1 - Robust measurement selection for biochemical pathway experimental design

AU - Brown, Martin

AU - He, Fei

AU - Yeung, Lam Fat

PY - 2008/11/8

Y1 - 2008/11/8

N2 - 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.

AB - 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.

KW - Experimental design

KW - Regularisation

KW - Sensitivity analysis

KW - Systems biology

KW - Taguchi design

UR - http://www.scopus.com/inward/record.url?scp=55849117400&partnerID=8YFLogxK

U2 - 10.1504/IJBRA.2008.021176

DO - 10.1504/IJBRA.2008.021176

M3 - Article

VL - 4

SP - 400

EP - 416

JO - International Journal of Bioinformatics Research and Applications

JF - International Journal of Bioinformatics Research and Applications

SN - 1744-5485

IS - 4

ER -