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BMCBI
2011
12 years 11 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
BMCBI
2006
106views more  BMCBI 2006»
13 years 7 months ago
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional nor
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...
Henrik Bengtsson, Ola Hössjer
CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
14 years 1 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
BMCBI
2010
176views more  BMCBI 2010»
13 years 7 months ago
Reverse engineering gene regulatory network from microarray data using linear time-variant model
nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
Mitra Kabir, Nasimul Noman, Hitoshi Iba
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin