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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2007
134views more  BMCBI 2007»
14 years 11 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2006
155views more  BMCBI 2006»
14 years 11 months ago
AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data
Background: DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challeng...
Guoqing Lu, The V. Nguyen, Yuannan Xia, Michael Fr...
101
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BMCBI
2008
138views more  BMCBI 2008»
14 years 11 months ago
Combining transcriptional datasets using the generalized singular value decomposition
Background: Both microarrays and quantitative real-time PCR are convenient tools for studying the transcriptional levels of genes. The former is preferable for large scale studies...
Andreas W. Schreiber, Neil J. Shirley, Rachel A. B...
127
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BMCBI
2006
183views more  BMCBI 2006»
14 years 11 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2008
160views more  BMCBI 2008»
14 years 11 months ago
A method for analyzing censored survival phenotype with gene expression data
Background: Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles a...
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Ch...