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BMCBI
2006
147views more  BMCBI 2006»
13 years 7 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2004
154views more  BMCBI 2004»
13 years 7 months ago
Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells
Background: cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accur...
Bin Yao, Sanjay N. Rakhade, Qunfang Li, Sharlin Ah...
BMCBI
2008
132views more  BMCBI 2008»
13 years 7 months ago
Very Important Pool (VIP) genes - an application for microarray-based molecular signatures
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...
BMCBI
2008
102views more  BMCBI 2008»
13 years 7 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
BMCBI
2010
124views more  BMCBI 2010»
13 years 7 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...