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BMCBI
2004
124views more  BMCBI 2004»
13 years 7 months ago
Tests for finding complex patterns of differential expression in cancers: towards individualized medicine
Background: Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g....
James Lyons-Weiler, Satish Patel, Michael J. Becic...
BMCBI
2007
134views more  BMCBI 2007»
13 years 7 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2002
195views more  BMCBI 2002»
13 years 7 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data
Background: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone ...
Benedikt Zacher, Pei Fen Kuan, Achim Tresch
TCBB
2008
107views more  TCBB 2008»
13 years 7 months ago
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering
It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Hyuk Cho, Inderjit S. Dhillon