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» Data-adaptive test statistics for microarray data
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BMCBI
2008
110views more  BMCBI 2008»
13 years 7 months ago
Testing for treatment effects on gene ontology
In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functi...
Taewon Lee, Varsha G. Desai, Cruz Velasco, Robert ...
BMCBI
2006
183views more  BMCBI 2006»
13 years 7 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
BMCBI
2008
95views more  BMCBI 2008»
13 years 7 months ago
Gene set analyses for interpreting microarray experiments on prokaryotic organisms
Background: Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Rece...
Nathan L. Tintle, Aaron A. Best, Matthew DeJongh, ...
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 7 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi