DocumentCode :
1150358
Title :
Multi-element probabilistic collocation for sensitivity analysis in cellular signalling networks
Author :
Foo, J. ; Sindi, S. ; Karniadakis, George E.
Author_Institution :
Div. of Appl. Math., Brown Univ., Providence, RI, USA
Volume :
3
Issue :
4
fYear :
2009
fDate :
7/1/2009 12:00:00 AM
Firstpage :
239
Lastpage :
254
Abstract :
The multi-element probabilistic collocation method (ME-PCM) as a tool for sensitivity analysis of differential equation models as applied to cellular signalling networks is formulated. This method utilises a simple, efficient sampling algorithm to quantify local sensitivities throughout the parameter space. The application of the ME-PCM to a previously published ordinary differential equation model of the apoptosis signalling network is presented. The authors verify agreement with the previously identified regions of sensitivity and then go on to analyse this region in greater detail with the ME-PCM. The authors demonstrate the generality of the ME-PCM by studying sensitivity of the system using a variety of biologically relevant markers in the system such as variation in one (or many) chemical species as a function of time, and total exposure of a single chemical species.
Keywords :
biology computing; cellular biophysics; differential equations; stochastic processes; apoptosis signalling network; cellular signalling networks; differential equation models; multielement probabilistic collocation method; sensitivity analysis;
fLanguage :
English
Journal_Title :
Systems Biology, IET
Publisher :
iet
ISSN :
1751-8849
Type :
jour
DOI :
10.1049/iet-syb.2008.0126
Filename :
5174553
Link To Document :
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