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» Evaluation of microarray data normalization procedures using...
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BMCBI
2004
127views more  BMCBI 2004»
13 years 4 months ago
Optimized LOWESS normalization parameter selection for DNA microarray data
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...
BMCBI
2005
126views more  BMCBI 2005»
13 years 4 months ago
An algorithm for automatic evaluation of the spot quality in two-color DNA microarray experiments
Background: Although DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experiment...
Eugene Novikov, Emmanuel Barillot
BMCBI
2004
106views more  BMCBI 2004»
13 years 4 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
BMCBI
2006
374views more  BMCBI 2006»
13 years 4 months ago
AMDA: an R package for the automated microarray data analysis
Background: Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and...
Mattia Pelizzola, Norman Pavelka, Maria Foti, Paol...
BMCBI
2010
153views more  BMCBI 2010»
13 years 4 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...