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dc.contributor.authorDu, Lipingen_US
dc.contributor.authorWu, Shuanhuen_US
dc.contributor.authorLiew, Alan Wee-Chungen_US
dc.contributor.authorSmith, David Keithen_US
dc.contributor.authorYan, Hongen_US
dc.date.accessioned2017-04-24T12:52:36Z
dc.date.available2017-04-24T12:52:36Z
dc.date.issued2006en_US
dc.date.modified2009-03-18T07:22:43Z
dc.identifier.issn03029743en_US
dc.identifier.doi10.1007/11875741_4en_AU
dc.identifier.urihttp://hdl.handle.net/10072/21794
dc.description.abstractSpectral analysis of DNA microarray gene expressions time series data is important for understanding the regulation of gene expression and gene function of the Plasmodium falciparum in the intraerythrocytic developmental cycle. In this paper, we propose a new strategy to analyze the cell cycle regulation of gene expression profiles based on the combination of singular spectrum analysis (SSA) and autoregressive (AR) spectral estimation. Using the SSA, we extract the dominant trend of data and reduce the effect of noise. Based on the AR analysis, high resolution spectra can be produced. Experiment results show that our method can extract more genes and the information can be useful for new drug design.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherSpringer Berlin / Heidelbergen_US
dc.publisher.placeGermanyen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom32en_US
dc.relation.ispartofpageto41en_US
dc.relation.ispartofjournalLecture Notes in Computer Scienceen_US
dc.relation.ispartofvolume4216en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode270201en_US
dc.subject.fieldofresearchcode280204en_US
dc.titleParametric Spectral Analysis of Malaria Gene Expression Time Series Dataen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.date.issued2006
gro.hasfulltextNo Full Text


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