Sciweavers

12 search results - page 2 / 3
» A power law global error model for the identification of dif...
Sort
View
CSDA
2007
151views more  CSDA 2007»
13 years 5 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
BMCBI
2010
115views more  BMCBI 2010»
13 years 5 months ago
Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...
BMCBI
2005
135views more  BMCBI 2005»
13 years 5 months ago
A robust two-way semi-linear model for normalization of cDNA microarray data
Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative e...
Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzel...
BMCBI
2008
124views more  BMCBI 2008»
13 years 5 months ago
A probe-treatment-reference (PTR) model for the analysis of oligonucleotide expression microarrays
Background: Microarray pre-processing usually consists of normalization and summarization. Normalization aims to remove non-biological variations across different arrays. The norm...
Huanying Ge, Chao Cheng, Lei M. Li
BMCBI
2007
86views more  BMCBI 2007»
13 years 5 months ago
Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of
Background: Deficiencies in microarray technology cause unwanted variation in the hybridization signal, obscuring the true measurements of intracellular transcript levels. Here we...
William O. Ward, Carol D. Swartz, Steffen Porwolli...