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» A New Hybrid Approach for Unsupervised Gene Selection
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BMCBI
2002
188views more  BMCBI 2002»
13 years 6 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...
DAM
2007
91views more  DAM 2007»
13 years 6 months ago
Integer linear programming approaches for non-unique probe selection
In addition to their prevalent use for analyzing gene expression, DNA microarrays are an efficient tool for biological, medical, and industrial applications because of their abil...
Gunnar W. Klau, Sven Rahmann, Alexander Schliep, M...
BMCBI
2006
198views more  BMCBI 2006»
13 years 6 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
BMCBI
2010
106views more  BMCBI 2010»
13 years 6 months ago
Selection of optimal reference genes for normalization in quantitative RT-PCR
Background: Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introdu...
Inna Chervoneva, Yanyan Li, Stephanie Schulz, Sean...
BMCBI
2004
79views more  BMCBI 2004»
13 years 6 months ago
A new mixture model approach to analyzing allelic-loss data using Bayes factors
Background: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor...
Manisha Desai, Mary J. Emond