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BMCBI
2008
114views more  BMCBI 2008»
13 years 7 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, ...
JMLR
2010
161views more  JMLR 2010»
13 years 2 months ago
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
BMCBI
2006
154views more  BMCBI 2006»
13 years 7 months ago
An improved procedure for gene selection from microarray experiments using false discovery rate criterion
Background: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are o...
James J. Yang, Mark C. K. Yang
BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Vector analysis as a fast and easy method to compare gene expression responses between different experimental backgrounds
Background: Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on ...
Rainer Breitling, Patrick Armengaud, Anna Amtmann
BMCBI
2005
163views more  BMCBI 2005»
13 years 7 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...