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Uncertain gene regulatory networks simplified by gramian-based approach.
In: Proceedings (2011 International Conference on Bioinformatics & Computational Biology (BIOCOMP '11), 18-21 July 2011, Las Vegas, USA). Athens, GA, USA: CSREA Press, 2012. 751-759
The complexity of gene regulatory networks described by coupled nonlinear differen- tial equations is often an obstacle for analysis purposes. They are prone to internal parametrical fluctuations making thus robustness a crucial property of these net- works to attenuate the effects of internal fluctuation. Therefore, the development of effective model reduction techniques for uncertain biological systems is of paramount importance in the field of systems biology. In this paper, we apply a Gramian-based approach for model reduction for gene regulatory networks based only on finding generalized Gramians and standard matrix transformations. The method is based on finding a generalized controllability and observability Gramian of the uncertain system and then based on a state transformation matrix a reduced-order representation. Under the assumption that the structured uncertainties are norm-bounded, we can prove that the reduced-order balanced system is also stable.
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Publication type
Article: Conference contribution
Editors
Arabnia, H.R.* ; Tran, Q.-N.*
Keywords
Gene regulatory network, uncertain system; model reduction
ISBN
1-60132-170-8
Conference Title
2011 International Conference on Bioinformatics & Computational Biology (BIOCOMP '11)
Conference Date
18-21 July 2011
Conference Location
Las Vegas, USA
Proceedings Title
Proceedings
Quellenangaben
Pages: 751-759
Publisher
CSREA Press
Publishing Place
Athens, GA, USA
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