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BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
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
104views more  BMCBI 2008»
13 years 7 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
BMCBI
2010
243views more  BMCBI 2010»
13 years 7 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
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