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» Improving gene set analysis of microarray data by SAM-GS
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BMCBI
2007
97views more  BMCBI 2007»
13 years 7 months ago
In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation
Background: Microarray co-expression signatures are an important tool for studying gene function and relations between genes. In addition to genuine biological co-expression, corr...
Tineke Casneuf, Yves Van de Peer, Wolfgang Huber
BMCBI
2008
135views more  BMCBI 2008»
13 years 7 months ago
Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...
BMCBI
2006
171views more  BMCBI 2006»
13 years 7 months ago
The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies
Background: Intensity values measured by Affymetrix microarrays have to be both normalized, to be able to compare different microarrays by removing non-biological variation, and s...
Roel G. W. Verhaak, Frank J. T. Staal, Peter J. M....
BMCBI
2008
134views more  BMCBI 2008»
13 years 7 months ago
Clustering cancer gene expression data: a comparative study
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...
Marcílio Carlos Pereira de Souto, Ivan G. C...
BMCBI
2008
121views more  BMCBI 2008»
13 years 7 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...