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Article: Construction and Control of Genetic Regulatory Networks: A Multivariate Markov Chain Approach

TitleConstruction and Control of Genetic Regulatory Networks: A Multivariate Markov Chain Approach
Authors
KeywordsGene Expression Sequences
Multivariate Markov Chain
Optimal Control Policy
Probabilistic Boolean Networks
Issue Date2008
PublisherScientific Research Publishing, Inc. The Journal's web site is located at http://www.scirp.org/journal/jbise/
Citation
Journal of Biomedical Science and Engineering, 2008, v. 1 n. 1, p. 15-21 How to Cite?
AbstractIn the post-genomic era, the construction and control of genetic regulatory networks using gene expression data is a hot research topic. Boolean networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) have been served as an effective tool for this purpose. However, PBNs are difficult to be used in practice when the number of genes is large because of the huge computational cost. In this paper, we propose a simplified multivariate Markov model for approximating a PBN The new model can preserve the strength of PBNs, the ability to capture the inter-dependence of the genes in the network, qnd at the same time reduce the complexity of the network and therefore the computational cost. We then present an optimal control model with hard constraints for the purpose of control/intervention of a genetic regulatory network. Numerical experimental examples based on the yeast data are given to demonstrate the effectiveness of our proposed model and control policy.
Persistent Identifierhttp://hdl.handle.net/10722/75318
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhang, SQen_HK
dc.contributor.authorChing, WKen_HK
dc.contributor.authorJiao, Yen_HK
dc.contributor.authorWu, LYen_HK
dc.contributor.authorChan, RHen_HK
dc.date.accessioned2010-09-06T07:09:59Z-
dc.date.available2010-09-06T07:09:59Z-
dc.date.issued2008en_HK
dc.identifier.citationJournal of Biomedical Science and Engineering, 2008, v. 1 n. 1, p. 15-21en_HK
dc.identifier.issn1937-6871en_HK
dc.identifier.urihttp://hdl.handle.net/10722/75318-
dc.description.abstractIn the post-genomic era, the construction and control of genetic regulatory networks using gene expression data is a hot research topic. Boolean networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) have been served as an effective tool for this purpose. However, PBNs are difficult to be used in practice when the number of genes is large because of the huge computational cost. In this paper, we propose a simplified multivariate Markov model for approximating a PBN The new model can preserve the strength of PBNs, the ability to capture the inter-dependence of the genes in the network, qnd at the same time reduce the complexity of the network and therefore the computational cost. We then present an optimal control model with hard constraints for the purpose of control/intervention of a genetic regulatory network. Numerical experimental examples based on the yeast data are given to demonstrate the effectiveness of our proposed model and control policy.-
dc.languageengen_HK
dc.publisherScientific Research Publishing, Inc. The Journal's web site is located at http://www.scirp.org/journal/jbise/en_HK
dc.relation.ispartofJournal of Biomedical Science and Engineeringen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectGene Expression Sequences-
dc.subjectMultivariate Markov Chain-
dc.subjectOptimal Control Policy-
dc.subjectProbabilistic Boolean Networks-
dc.titleConstruction and Control of Genetic Regulatory Networks: A Multivariate Markov Chain Approachen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1937-6871&volume=1&spage=15&epage=21&date=2008&atitle=Construction+and+Control+of+Genetic+Regulatory+Networks:+A+Multivariate+Markov+Chain+Approachen_HK
dc.identifier.emailChing, WK: wching@hkucc.hku.hken_HK
dc.identifier.emailJiao, Y: jiaoyue@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.4236/jbise.2008.11003-
dc.identifier.hkuros141942en_HK
dc.identifier.volume1-
dc.identifier.issue1-
dc.identifier.spage15-
dc.identifier.epage21-
dc.publisher.placeUnited States-

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