Sciweavers

799 search results - page 11 / 160
» A stable gene selection in microarray data analysis
Sort
View
BMCBI
2005
212views more  BMCBI 2005»
13 years 7 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 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
2006
97views more  BMCBI 2006»
13 years 7 months ago
Selecting normalization genes for small diagnostic microarrays
Background: Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. T...
Jochen Jaeger, Rainer Spang
ISMDA
2005
Springer
14 years 1 months ago
Relevance, Redundancy and Differential Prioritization in Feature Selection for Multiclass Gene Expression Data
The large number of genes in microarray data makes feature selection techniques more crucial than ever. From various ranking-based filter procedures to classifier-based wrapper tec...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BMCBI
2008
167views more  BMCBI 2008»
13 years 7 months ago
Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments
Background: Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to enviro...
Stefano Parodi, Vito Pistoia, Marco Muselli