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Article: Modeling Genetic Regulatory Networks: A Delay Discrete Dynamical Model Approach
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TitleModeling Genetic Regulatory Networks: A Delay Discrete Dynamical Model Approach
 
AuthorsJiang, H1
Ching, WK1
Aoki-Kinoshita, K
Guo, D3
 
KeywordsDelay effects
Discrete dynamic system
Genetic regulatory networks
K-means clustering method
Linear multiple regression
 
Issue Date2012
 
PublisherSpringer Verlag. The Journal's web site is located at http://link.springer.com/journal/11424
 
CitationJournal of Systems Science and Complexity, 2012, v. 25 n. 6, p. 1052-1067 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11424-012-0283-2
 
AbstractModeling genetic regulatory networks is an important research topic in genomic research and computational systems biology. This paper considers the problem of constructing a genetic regulatory network (GRN) using the discrete dynamic system (DDS) model approach. Although considerable research has been devoted to building GRNs, many of the works did not consider the time-delay effect. Here, the authors propose a time-delay DDS model composed of linear difference equations to represent temporal interactions among significantly expressed genes. The authors also introduce interpolation scheme and re-sampling method for equalizing the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed genetic network using linear multiple regression matches with the original data very well. Simulation results are given to demonstrate the effectiveness of the proposed method and model. © 2012 Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg.
 
ISSN1009-6124
2012 Impact Factor: 0.263
2012 SCImago Journal Rankings: 0.352
 
DOIhttp://dx.doi.org/10.1007/s11424-012-0283-2
 
DC FieldValue
dc.contributor.authorJiang, H
 
dc.contributor.authorChing, WK
 
dc.contributor.authorAoki-Kinoshita, K
 
dc.contributor.authorGuo, D
 
dc.date.accessioned2012-09-20T07:56:20Z
 
dc.date.available2012-09-20T07:56:20Z
 
dc.date.issued2012
 
dc.description.abstractModeling genetic regulatory networks is an important research topic in genomic research and computational systems biology. This paper considers the problem of constructing a genetic regulatory network (GRN) using the discrete dynamic system (DDS) model approach. Although considerable research has been devoted to building GRNs, many of the works did not consider the time-delay effect. Here, the authors propose a time-delay DDS model composed of linear difference equations to represent temporal interactions among significantly expressed genes. The authors also introduce interpolation scheme and re-sampling method for equalizing the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed genetic network using linear multiple regression matches with the original data very well. Simulation results are given to demonstrate the effectiveness of the proposed method and model. © 2012 Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg.
 
dc.identifier.citationJournal of Systems Science and Complexity, 2012, v. 25 n. 6, p. 1052-1067 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11424-012-0283-2
 
dc.identifier.doihttp://dx.doi.org/10.1007/s11424-012-0283-2
 
dc.identifier.epage1067
 
dc.identifier.hkuros208786
 
dc.identifier.issn1009-6124
2012 Impact Factor: 0.263
2012 SCImago Journal Rankings: 0.352
 
dc.identifier.issue6
 
dc.identifier.scopuseid_2-s2.0-84871843955
 
dc.identifier.spage1052
 
dc.identifier.urihttp://hdl.handle.net/10722/164184
 
dc.identifier.volume25
 
dc.languageeng
 
dc.publisherSpringer Verlag. The Journal's web site is located at http://link.springer.com/journal/11424
 
dc.publisher.placeChina
 
dc.relation.ispartofJournal of Systems Science and Complexity
 
dc.rightsThe original publication is available at www.springerlink.com
 
dc.subjectDelay effects
 
dc.subjectDiscrete dynamic system
 
dc.subjectGenetic regulatory networks
 
dc.subjectK-means clustering method
 
dc.subjectLinear multiple regression
 
dc.titleModeling Genetic Regulatory Networks: A Delay Discrete Dynamical Model Approach
 
dc.typeArticle
 
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<contributor.author>Ching, WK</contributor.author>
<contributor.author>Aoki-Kinoshita, K</contributor.author>
<contributor.author>Guo, D</contributor.author>
<date.accessioned>2012-09-20T07:56:20Z</date.accessioned>
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<description.abstract>Modeling genetic regulatory networks is an important research topic in genomic research and computational systems biology. This paper considers the problem of constructing a genetic regulatory network (GRN) using the discrete dynamic system (DDS) model approach. Although considerable research has been devoted to building GRNs, many of the works did not consider the time-delay effect. Here, the authors propose a time-delay DDS model composed of linear difference equations to represent temporal interactions among significantly expressed genes. The authors also introduce interpolation scheme and re-sampling method for equalizing the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed genetic network using linear multiple regression matches with the original data very well. Simulation results are given to demonstrate the effectiveness of the proposed method and model. &#169; 2012 Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg.</description.abstract>
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<subject>Delay effects</subject>
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Author Affiliations
  1. The University of Hong Kong
  2. Soka University
  3. Chinese University of Hong Kong