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