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BMCBI
2010
124views more  BMCBI 2010»
13 years 6 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
BMCBI
2008
96views more  BMCBI 2008»
13 years 6 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...
BMCBI
2007
110views more  BMCBI 2007»
13 years 6 months ago
Selection of long oligonucleotides for gene expression microarrays using weighted rank-sum strategy
Background: The design of long oligonucleotides for spotted DNA microarrays requires detailed attention to ensure their optimal performance in the hybridization process. The main ...
Guangan Hu, Manuel Llinás, Jingguang Li, Pe...
BMCBI
2010
80views more  BMCBI 2010»
13 years 6 months ago
Power and sample size estimation in microarray studies
Background: Before conducting a microarray experiment, one important issue that needs to be determined is the number of arrays required in order to have adequate power to identify...
Wei-Jiun Lin, Huey-miin Hsueh, James J. Chen
JBI
2008
159views Bioinformatics» more  JBI 2008»
13 years 6 months ago
SEGS: Search for enriched gene sets in microarray data
Gene Ontology (GO) terms are often used to interpret the results of microarray experiments. The most common approach is to perform Fisher's exact tests to find gene sets anno...
Igor Trajkovski, Nada Lavrac, Jakub Tolar