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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2006
200views more  BMCBI 2006»
13 years 6 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
BMCBI
2007
149views more  BMCBI 2007»
13 years 6 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
BMCBI
2004
75views more  BMCBI 2004»
13 years 6 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
WCE
2007
13 years 7 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
BMCBI
2007
149views more  BMCBI 2007»
13 years 6 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin