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A novel statistical model for finding patterns in cell-cycle transcription data

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dc.contributor.authorPittelkow, Yvonne
dc.contributor.authorWilson, Susan
dc.date.accessioned2015-12-10T22:20:04Z
dc.date.issued2010
dc.date.updated2016-02-24T08:25:02Z
dc.description.abstractA new statistical model is developed for finding patterns in gene expression data from time course experiments. Using a recent data set, it is demonstrated how iteratively applying this model simultaneously with visualisation tools gives further, useful information.
dc.identifier.issn0167-8655
dc.identifier.urihttp://hdl.handle.net/1885/51777
dc.publisherElsevier
dc.sourcePattern Recognition Letters
dc.subjectKeywords: Absolute sine model; Biplots; Gene expression microarrays; h-Profile plots; Periodic genes; Time-course experiments; Experiments; Genes; Microarrays; Visualization; Transcription Absolute sine model; Covariance biplots; Gene expression microarrays; h-Profile plots; Periodic genes; Time course experiment
dc.titleA novel statistical model for finding patterns in cell-cycle transcription data
dc.typeJournal article
local.bibliographicCitation.issue14
local.bibliographicCitation.lastpage2132
local.bibliographicCitation.startpage2126
local.contributor.affiliationPittelkow, Yvonne, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationWilson, Susan, College of Physical and Mathematical Sciences, ANU
local.contributor.authoruidPittelkow, Yvonne, u7500275
local.contributor.authoruidWilson, Susan, u7401449
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010401 - Applied Statistics
local.identifier.ariespublicationf2965xPUB232
local.identifier.citationvolume31
local.identifier.doi10.1016/j.patrec.2009.11.015
local.identifier.scopusID2-s2.0-77956341695
local.identifier.thomsonID000282384500007
local.type.statusPublished Version

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