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» Adjustment of systematic microarray data biases
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BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
BMCBI
2007
99views more  BMCBI 2007»
13 years 7 months ago
Orthogonal projections to latent structures as a strategy for microarray data normalization
Background: During generation of microarray data, various forms of systematic biases are frequently introduced which limits accuracy and precision of the results. In order to prop...
Max Bylesjö, Daniel Eriksson, Andreas Sjö...
BMCBI
2010
89views more  BMCBI 2010»
13 years 7 months ago
Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays
Background: Microarray measurements are susceptible to a variety of experimental artifacts, some of which give rise to systematic biases that are spatially dependent in a unique w...
High-Seng Chai, Terry M. Therneau, Kent R. Bailey,...
BMCBI
2008
128views more  BMCBI 2008»
13 years 7 months ago
Improving the prediction accuracy in classification using the combined data sets by ranks of gene expressions
Background: The information from different data sets experimented under different conditions may be inconsistent even though they are performed with the same research objectives. ...
Ki-Yeol Kim, Dong Hyuk Ki, Hei-Cheul Jeung, Hyun C...
BMCBI
2004
161views more  BMCBI 2004»
13 years 7 months ago
Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatme
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Tomokazu Konishi