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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2007
176views more  BMCBI 2007»
14 years 10 months ago
Genome Expression Pathway Analysis Tool - Analysis and visualization of microarray gene expression data under genomic, proteomic
Background: Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be use...
Markus Weniger, Julia C. Engelmann, Jörg Schu...
BMCBI
2005
212views more  BMCBI 2005»
14 years 9 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
BMCBI
2007
149views more  BMCBI 2007»
14 years 10 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
BIOINFORMATICS
2005
105views more  BIOINFORMATICS 2005»
14 years 9 months ago
MADE4: an R package for multivariate analysis of gene expression data
Summary: MADE4, microarray ade4, is a software package that facilitates multivariate analysis of microarray gene expression data. MADE4 accepts a wide variety of gene expression d...
Aedín C. Culhane, Jean Thioulouse, Guy Perr...
BMCBI
2004
139views more  BMCBI 2004»
14 years 9 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend