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JCB
2002
93views more  JCB 2002»
13 years 7 months ago
Unfolding of Microarray Data
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
CSDA
2007
151views more  CSDA 2007»
13 years 7 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
BIOINFORMATICS
2005
72views more  BIOINFORMATICS 2005»
13 years 7 months ago
Use of within-array replicate spots for assessing differential expression in microarray experiments
Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
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
165views more  BMCBI 2006»
13 years 8 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