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» Two-phase clustering strategy for gene expression data sets
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BMCBI
2006
120views more  BMCBI 2006»
14 years 9 months ago
An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
Ryung S. Kim, Hongkai Ji, Wing Hung Wong
BMCBI
2008
117views more  BMCBI 2008»
14 years 9 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...
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BMCBI
2007
112views more  BMCBI 2007»
14 years 9 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
BMCBI
2006
203views more  BMCBI 2006»
14 years 9 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
BMCBI
2006
129views more  BMCBI 2006»
14 years 9 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer