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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2007
239views more  BMCBI 2007»
14 years 10 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
113views more  BMCBI 2004»
14 years 9 months ago
Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide array
Background: To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summar...
Leah Barrera, Chris Benner, Yong-Chuan Tao, Elizab...
BMCBI
2005
124views more  BMCBI 2005»
14 years 9 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
BMCBI
2008
115views more  BMCBI 2008»
14 years 10 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
BMCBI
2008
99views more  BMCBI 2008»
14 years 10 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu