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Conference Paper: An efficient convex nonnegative network component analysis for gene regulatory network reconstruction

TitleAn efficient convex nonnegative network component analysis for gene regulatory network reconstruction
Authors
KeywordsConvex programming
Gene regulatory network
Microarray
Network component analysis
Positivity constraints
Issue Date2009
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, UK., 7-9 September 2009. In Lecture Notes in Computer Science, 2009, v. 5780, p. 56-66 How to Cite?
AbstractA systems biology problem of reconstructing gene regulatory network from time-course gene expression microarray data via network component analysis (NCA) is investigated in this paper. Inspired by the idea that each column of the connectivity matrix can be estimated independently, we try to propose a fast and stable convex approach for nonnegative NCA (nnNCA). Compared with the existing method, our new method reduces the computational cost substantially, whereas maintains a reasonable accuracy. Both the simulation results and experimental results demonstrate the effectiveness of our method. © 2009 Springer Berlin Heidelberg.
DescriptionLNCS v. 5780 entitled: Pattern recognition in bioinformatics [electronic resource] : 4th IAPR international conference, PRIB 2009 ... : proceedings
Persistent Identifierhttp://hdl.handle.net/10722/99225
ISBN
ISSN
2020 SCImago Journal Rankings: 0.249
References

 

DC FieldValueLanguage
dc.contributor.authorDai, Jen_HK
dc.contributor.authorChang, Cen_HK
dc.contributor.authorYe, Zen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2010-09-25T18:20:56Z-
dc.date.available2010-09-25T18:20:56Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, UK., 7-9 September 2009. In Lecture Notes in Computer Science, 2009, v. 5780, p. 56-66en_HK
dc.identifier.isbn978-3-642-04030-6-
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/99225-
dc.descriptionLNCS v. 5780 entitled: Pattern recognition in bioinformatics [electronic resource] : 4th IAPR international conference, PRIB 2009 ... : proceedings-
dc.description.abstractA systems biology problem of reconstructing gene regulatory network from time-course gene expression microarray data via network component analysis (NCA) is investigated in this paper. Inspired by the idea that each column of the connectivity matrix can be estimated independently, we try to propose a fast and stable convex approach for nonnegative NCA (nnNCA). Compared with the existing method, our new method reduces the computational cost substantially, whereas maintains a reasonable accuracy. Both the simulation results and experimental results demonstrate the effectiveness of our method. © 2009 Springer Berlin Heidelberg.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectConvex programmingen_HK
dc.subjectGene regulatory networken_HK
dc.subjectMicroarrayen_HK
dc.subjectNetwork component analysisen_HK
dc.subjectPositivity constraintsen_HK
dc.titleAn efficient convex nonnegative network component analysis for gene regulatory network reconstructionen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChang, C: cqchang@eee.hku.hken_HK
dc.identifier.emailHung, YS: yshung@hkucc.hku.hken_HK
dc.identifier.authorityChang, C=rp00095en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-642-04031-3_6en_HK
dc.identifier.scopuseid_2-s2.0-70349871612en_HK
dc.identifier.hkuros165287en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349871612&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5780en_HK
dc.identifier.spage56en_HK
dc.identifier.epage66en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.scopusauthoridYe, Z=7401957018en_HK
dc.identifier.scopusauthoridChang, C=7407033052en_HK
dc.identifier.scopusauthoridDai, J=26421945900en_HK
dc.customcontrol.immutablesml 140529-
dc.identifier.issnl0302-9743-

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