Mining biological information from 3D gene expression data : the OPTricluster algorithm

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DOIResolve DOI: http://doi.org/10.1186/1471-2105-13-54
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TypeArticle
Journal titleBMC Bioinformatics 2012
Volume13
Pages54
AbstractBackground: Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; NRC Plant Biotechnology Institute; National Research Council Canada
Peer reviewedYes
NPARC number20262885
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Record identifier23c1f50e-c76a-4c55-9354-84e8181343f4
Record created2012-07-10
Record modified2016-05-09
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