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» Analysis of variance components in gene expression data
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CSB
2005
IEEE
146views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
Sun-Yuan Kung, Man-Wai Mak, Ilias Tagkopoulos
BMCBI
2007
134views more  BMCBI 2007»
14 years 9 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
14 years 11 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
CINQ
2004
Springer
116views Database» more  CINQ 2004»
15 years 1 months ago
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining
Abstract. One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is e...
Ruggero G. Pensa, Jérémy Besson, C&e...
ISBI
2004
IEEE
15 years 10 months ago
Microarray Gene Expression Data Analysis
Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of ...
Yuhua Ding, Jacqueline Fairley, George J. Vachtsev...