Name
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 IkappaBalpha - NF - kappaB 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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1504/IJBRA.2008.021176 | IJBRA |
Keywords | Field | DocType |
time-seriesexperimental design,robust experimental design strategy,biochemical pathway experimental design,regularisation-based design method,similar uniform design result,b signallingpathway system,taguchi-based design approach,large parametric uncertainty,design approach,thatdifferent parametric uncertainty,robust measurement selection,current systemsbiology research,systems biology,experimental design,bioinformatics,taguchi methods,optimal design,sensitivity analysis | Econometrics,Mathematical optimization,Robust design,Uniform design,Biology,Systems biology,Optimal design,Parametric statistics,Taguchi methods,Observer (quantum physics),Genetics | Journal |
Volume | Issue | ISSN |
4 | 4 | 1744-5485 |
Citations | PageRank | References |
4 | 0.59 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M Brown | 1 | 106 | 15.73 |
| Fei He | 2 | 32 | 13.85 |
| Lam Fat Yeung | 3 | 20 | 5.39 |