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» Normalization for triple-target microarray experiments
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SAC
2006
ACM
14 years 1 months ago
Two-phase clustering strategy for gene expression data sets
In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and con...
Dirk Habich, Thomas Wächter, Wolfgang Lehner,...
BMCBI
2007
173views more  BMCBI 2007»
13 years 7 months ago
Ringo - an R/Bioconductor package for analyzing ChIP-chip readouts
Background: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modi...
Joern Toedling, Oleg Sklyar, Tammo Krueger, Jenny ...
BMCBI
2006
158views more  BMCBI 2006»
13 years 7 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
BMCBI
2010
181views more  BMCBI 2010»
13 years 7 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2004
128views more  BMCBI 2004»
13 years 7 months ago
Comparing transformation methods for DNA microarray data
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Helene H. Thygesen, Aeilko H. Zwinderman