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» Analysis of Variance for Gene Expression Microarray Data
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JIPS
2007
134views more  JIPS 2007»
14 years 9 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...
BMCBI
2004
150views more  BMCBI 2004»
14 years 9 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
BMCBI
2010
125views more  BMCBI 2010»
14 years 10 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
BMCBI
2002
94views more  BMCBI 2002»
14 years 9 months ago
Computational method for reducing variance with Affymetrix microarrays
Background: Affymetrix microarrays are used by many laboratories to generate gene expression
Stephen Welle, Andrew I. Brooks, Charles A. Thornt...
BMCBI
2005
167views more  BMCBI 2005»
14 years 9 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors