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» Analysis of Variance for Gene Expression Microarray Data
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SAC
2006
ACM
15 years 5 months ago
Two-phase clustering strategy for gene expression data sets
In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and con...
Dirk Habich, Thomas Wächter, Wolfgang Lehner,...
BMCBI
2007
97views more  BMCBI 2007»
15 years 10 hour 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
138views more  BMCBI 2008»
15 years 8 hour ago
M-BISON: Microarray-based integration of data sources using networks
Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variabi...
Bernie J. Daigle Jr., Russ B. Altman
BMCBI
2006
131views more  BMCBI 2006»
14 years 12 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
BMCBI
2007
194views more  BMCBI 2007»
15 years 11 hour ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung