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Article: On the transient and steady-state estimates of interval genetic regulatory networks

TitleOn the transient and steady-state estimates of interval genetic regulatory networks
Authors
KeywordsExponential estimate
Genetic regulatory network (GRN)
Interval system
Steady-state estimate
Stochastic perturbation
Issue Date2010
PublisherIEEE.
Citation
Ieee Transactions On Systems, Man, And Cybernetics, Part B: Cybernetics, 2010, v. 40 n. 2, p. 336-349 How to Cite?
AbstractThis paper is concerned with the transient and steady-state estimates of a class of genetic regulatory networks (GRNs). Some sufficient conditions, which do not only present the transient estimate but also provide the estimates of decay rate and decay coefficient of the GRN with interval parameter uncertainties (interval GRN), are established by means of linear matrix inequality (LMI) and LyapunovKrasovskii functional. Moreover, the steady-state estimate of the proposed GRN model is also investigated. Furthermore, it is well known that gene regulation is an intrinsically noisy process due to intracellular and extracellular noise perturbations and environmental fluctuations. Then, by utilizing stochastic differential equation theory, the obtained results are extended to the case with noise perturbations due to natural random fluctuations. All the conditions are expressed within the framework of LMIs, which can easily be computed by using standard numerical software. A three-gene network is provided to illustrate the effectiveness of the theoretical results. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/124845
ISSN
2014 Impact Factor: 6.220
ISI Accession Number ID
Funding AgencyGrant Number
RGC HKU7031/06P
Funding Information:

Manuscript received November 15, 2008; revised February 26, 2009. First published October 23, 2009; current version published March 17, 2010. This work was supported in part by RGC HKU 7031/06P. This paper was recommended by Associate Editor H. Gao.

References

 

DC FieldValueLanguage
dc.contributor.authorLi, Pen_HK
dc.contributor.authorLam, Jen_HK
dc.contributor.authorShu, Zen_HK
dc.date.accessioned2010-10-31T10:57:24Z-
dc.date.available2010-10-31T10:57:24Z-
dc.date.issued2010en_HK
dc.identifier.citationIeee Transactions On Systems, Man, And Cybernetics, Part B: Cybernetics, 2010, v. 40 n. 2, p. 336-349en_HK
dc.identifier.issn1083-4419en_HK
dc.identifier.urihttp://hdl.handle.net/10722/124845-
dc.description.abstractThis paper is concerned with the transient and steady-state estimates of a class of genetic regulatory networks (GRNs). Some sufficient conditions, which do not only present the transient estimate but also provide the estimates of decay rate and decay coefficient of the GRN with interval parameter uncertainties (interval GRN), are established by means of linear matrix inequality (LMI) and LyapunovKrasovskii functional. Moreover, the steady-state estimate of the proposed GRN model is also investigated. Furthermore, it is well known that gene regulation is an intrinsically noisy process due to intracellular and extracellular noise perturbations and environmental fluctuations. Then, by utilizing stochastic differential equation theory, the obtained results are extended to the case with noise perturbations due to natural random fluctuations. All the conditions are expressed within the framework of LMIs, which can easily be computed by using standard numerical software. A three-gene network is provided to illustrate the effectiveness of the theoretical results. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.-
dc.relation.ispartofIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cyberneticsen_HK
dc.rights©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectExponential estimateen_HK
dc.subjectGenetic regulatory network (GRN)en_HK
dc.subjectInterval systemen_HK
dc.subjectSteady-state estimateen_HK
dc.subjectStochastic perturbationen_HK
dc.subject.meshAlgorithms-
dc.subject.meshComputer Simulation-
dc.subject.meshGene Regulatory Networks-
dc.subject.meshModels, Genetic-
dc.subject.meshSystems Biology - methods-
dc.titleOn the transient and steady-state estimates of interval genetic regulatory networksen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1083-4419&volume=40&issue=2&spage=336&epage=349&date=2010&atitle=On+the+transient+and+steady-state+estimates+of+interval+genetic+regulatory+networks-
dc.identifier.emailLam, J:james.lam@hku.hken_HK
dc.identifier.authorityLam, J=rp00133en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TSMCB.2009.2022402en_HK
dc.identifier.pmid19858029-
dc.identifier.scopuseid_2-s2.0-77949773421en_HK
dc.identifier.hkuros179617en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77949773421&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume40en_HK
dc.identifier.issue2en_HK
dc.identifier.spage336en_HK
dc.identifier.epage349en_HK
dc.identifier.isiWOS:000275665300005-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLi, P=35069715100en_HK
dc.identifier.scopusauthoridLam, J=7201973414en_HK
dc.identifier.scopusauthoridShu, Z=25652150400en_HK
dc.identifier.issnl1083-4419-

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