DocumentCode :
115161
Title :
On projection-based model reduction of biochemical networks part I: The deterministic case
Author :
Sootla, Aivar ; Anderson, James
Author_Institution :
Dept. of Bioeng., Imperial Coll. London, London, UK
fYear :
2014
fDate :
15-17 Dec. 2014
Firstpage :
3615
Lastpage :
3620
Abstract :
This paper addresses the problem of model reduction for dynamical system models that describe biochemical reaction networks. Inherent in such models are properties such as stability, positivity and network structure. Ideally these properties should be preserved by model reduction procedures, although traditional projection based approaches struggle to do this. We propose a projection based model reduction algorithm which uses generalised block diagonal Gramians to preserve structure and positivity. Two algorithms are presented, one provides more accurate reduced order models, the second provides easier to simulate reduced order models.
Keywords :
biochemistry; reduced order systems; stability; stochastic systems; time-varying systems; biochemical reaction networks; dynamical system models; generalised block diagonal Gramians; network structure; positivity; projection based model reduction algorithm; stability; stochastic systems; Biological system modeling; Computational modeling; Mathematical model; Reduced order systems; Standards; Steady-state; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
Type :
conf
DOI :
10.1109/CDC.2014.7039951
Filename :
7039951
Link To Document :
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