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» Stratification bias in low signal microarray studies
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BMCBI
2008
112views more  BMCBI 2008»
14 years 9 months ago
Normalization for triple-target microarray experiments
Background: Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the ...
Marie-Laure Martin-Magniette, Julie Aubert, Avner ...
BMCBI
2007
239views more  BMCBI 2007»
14 years 9 months ago
Pre-processing Agilent microarray data
Background: Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to...
Marianna Zahurak, Giovanni Parmigiani, Wayne Yu, R...
BMCBI
2004
158views more  BMCBI 2004»
14 years 9 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
BMCBI
2010
105views more  BMCBI 2010»
14 years 9 months ago
Effects of scanning sensitivity and multiple scan algorithms on microarray data quality
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Andrew Williams, Errol M. Thomson
BMCBI
2008
159views more  BMCBI 2008»
14 years 9 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...