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JCB
2002
93views more  JCB 2002»
14 years 9 months ago
Unfolding of Microarray Data
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
BMCBI
2006
213views more  BMCBI 2006»
14 years 9 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
92
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BMCBI
2010
129views more  BMCBI 2010»
14 years 9 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
IJBRA
2007
97views more  IJBRA 2007»
14 years 9 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...
BMCBI
2005
110views more  BMCBI 2005»
14 years 9 months ago
Considerations when using the significance analysis of microarrays (SAM) algorithm
Background: Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments...
Ola Larsson, Claes Wahlestedt, James A. Timmons