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» A stable gene selection in microarray data analysis
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BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park
BMCBI
2006
155views more  BMCBI 2006»
13 years 7 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...
BMCBI
2005
137views more  BMCBI 2005»
13 years 7 months ago
ArrayQuest: a web resource for the analysis of DNA microarray data
Background: Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow...
Gary L. Argraves, Saurin D. Jani, Jeremy L. Barth,...
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 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