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BMCBI
2008
133views more  BMCBI 2008»
13 years 7 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
BIOINFORMATICS
2005
134views more  BIOINFORMATICS 2005»
13 years 7 months ago
Outcome signature genes in breast cancer: is there a unique set?
Motivation: direct bearing whose expres Sorlie et al., 2 gene sets is a diseases (Lossos et al., 2004; Miklos and Maleszka, 2004), and the variables that could account questions i...
Liat Ein-Dor, Itai Kela, Gad Getz, David Givol, Ey...
BMCBI
2010
214views more  BMCBI 2010»
13 years 7 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
BMCBI
2006
129views more  BMCBI 2006»
13 years 7 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer