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» Combined Gene Selection Methods for Microarray Data Analysis
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125
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BMCBI
2005
126views more  BMCBI 2005»
15 years 2 months ago
Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models
Background: With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases...
Pingzhao Hu, Celia M. T. Greenwood, Joseph Beyene
123
Voted
BMCBI
2006
173views more  BMCBI 2006»
15 years 2 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
141
Voted
BMCBI
2010
243views more  BMCBI 2010»
15 years 2 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
BMCBI
2008
114views more  BMCBI 2008»
15 years 2 months ago
A visual analytics approach for understanding biclustering results from microarray data
Background: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from mi...
Rodrigo Santamaría, Roberto Therón, ...
BMCBI
2007
134views more  BMCBI 2007»
15 years 2 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...