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BMCBI
2007
173views more  BMCBI 2007»
13 years 8 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
BMCBI
2007
62views more  BMCBI 2007»
13 years 8 months ago
Missing channels in two-colour microarray experiments: Combining single-channel and two-channel data
Background: There are mechanisms, notably ozone degradation, that can damage a single channel of two-channel microarray experiments. Resulting analyses therefore often choose betw...
Andy G. Lynch, David E. Neal, John D. Kelly, Glyn ...
BMCBI
2008
96views more  BMCBI 2008»
13 years 8 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...
BMCBI
2010
100views more  BMCBI 2010»
13 years 8 months ago
A robust method for estimating gene expression states using Affymetrix microarray probe level data
Background: Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-speci...
Megu Ohtaki, Keiko Otani, Keiko Hiyama, Naomi Kame...