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Article: Robustness analysis of genetic regulatory networks affected by model uncertainty
Title | Robustness analysis of genetic regulatory networks affected by model uncertainty |
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Authors | |
Keywords | Genetic regulatory network Model uncertainty Robustness Stability |
Issue Date | 2011 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica |
Citation | Automatica, 2011, v. 47 n. 6, p. 1131-1138 How to Cite? |
Abstract | A fundamental problem in systems biology consists of investigating robustness properties of genetic regulatory networks (GRNs) with respect to model uncertainty. This paper addresses this problem for GRNs where the coefficients are rationally affected by polytopic uncertainty, and where the saturation functions are not exactly known. First, it is shown that a condition for ensuring that the GRN has a globally asymptotically stable equilibrium point for all admissible uncertainties can be obtained in terms of a convex optimization problem with linear matrix inequalities (LMIs), hence generalizing existing results that mainly consider only the case of GRNs where the coefficients are linearly affected by the uncertainty and the regulatory functions are in SUM form. Second, the problem of estimating the worst-case convergence rate of the trajectories to the equilibrium point over all admissible uncertainties is considered, and it is shown that a lower bound of this rate can be computed by solving a quasi-convex optimization problem with LMIs. Third, the paper considers the problem of estimating the set of uncertainties for which the GRN has a globally asymptotically stable equilibrium point. This problem is addressed, first, by showing how one can compute estimates with fixed shape by solving a quasi-convex optimization problem with LMIs, and second, by deriving a procedure for computing estimates with variable shape. Numerical examples illustrate the use of the proposed techniques. © 2010 Elsevier Ltd. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/135120 |
ISSN | 2023 Impact Factor: 4.8 2023 SCImago Journal Rankings: 3.502 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
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dc.contributor.author | Chesi, G | en_HK |
dc.date.accessioned | 2011-07-27T01:28:32Z | - |
dc.date.available | 2011-07-27T01:28:32Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Automatica, 2011, v. 47 n. 6, p. 1131-1138 | en_HK |
dc.identifier.issn | 0005-1098 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/135120 | - |
dc.description.abstract | A fundamental problem in systems biology consists of investigating robustness properties of genetic regulatory networks (GRNs) with respect to model uncertainty. This paper addresses this problem for GRNs where the coefficients are rationally affected by polytopic uncertainty, and where the saturation functions are not exactly known. First, it is shown that a condition for ensuring that the GRN has a globally asymptotically stable equilibrium point for all admissible uncertainties can be obtained in terms of a convex optimization problem with linear matrix inequalities (LMIs), hence generalizing existing results that mainly consider only the case of GRNs where the coefficients are linearly affected by the uncertainty and the regulatory functions are in SUM form. Second, the problem of estimating the worst-case convergence rate of the trajectories to the equilibrium point over all admissible uncertainties is considered, and it is shown that a lower bound of this rate can be computed by solving a quasi-convex optimization problem with LMIs. Third, the paper considers the problem of estimating the set of uncertainties for which the GRN has a globally asymptotically stable equilibrium point. This problem is addressed, first, by showing how one can compute estimates with fixed shape by solving a quasi-convex optimization problem with LMIs, and second, by deriving a procedure for computing estimates with variable shape. Numerical examples illustrate the use of the proposed techniques. © 2010 Elsevier Ltd. All rights reserved. | en_HK |
dc.language | eng | en_US |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica | en_HK |
dc.relation.ispartof | Automatica | en_HK |
dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication in Automatica. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Automatica, 2011, v. 47 n. 6, p. 1131-1138. DOI: 10.1016/j.automatica.2010.10.012 | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Genetic regulatory network | en_HK |
dc.subject | Model uncertainty | en_HK |
dc.subject | Robustness | en_HK |
dc.subject | Stability | en_HK |
dc.title | Robustness analysis of genetic regulatory networks affected by model uncertainty | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0005-1098&volume=47&issue=6&spage=1131&epage=1138&date=2011&atitle=Robustness+analysis+of+genetic+regulatory+networks+affected+by+model+uncertainty | - |
dc.identifier.email | Chesi, G:chesi@eee.hku.hk | en_HK |
dc.identifier.authority | Chesi, G=rp00100 | en_HK |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.automatica.2010.10.012 | en_HK |
dc.identifier.scopus | eid_2-s2.0-79956213939 | en_HK |
dc.identifier.hkuros | 187533 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79956213939&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 47 | en_HK |
dc.identifier.issue | 6 | en_HK |
dc.identifier.spage | 1131 | en_HK |
dc.identifier.epage | 1138 | en_HK |
dc.identifier.isi | WOS:000291456100006 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.identifier.scopusauthorid | Chesi, G=7006328614 | en_HK |
dc.identifier.citeulike | 8409716 | - |
dc.identifier.issnl | 0005-1098 | - |