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» Clustering cancer gene expression data: a comparative study
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BMCBI
2011
14 years 10 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
BMCBI
2007
104views more  BMCBI 2007»
15 years 6 months ago
Comparative evaluation of gene-set analysis methods
Background: Multiple data-analytic methods have been proposed for evaluating gene-expression levels in specific biological pathways, assessing differential expression associated w...
Qi Liu, Irina Dinu, Adeniyi J. Adewale, John D. Po...
BMCBI
2004
94views more  BMCBI 2004»
15 years 6 months ago
The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource
Background: Tissue Microarrays (TMAs) have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single sli...
Jules J. Berman, Milton Datta, Andre Kajdacsy-Ball...
BMCBI
2008
122views more  BMCBI 2008»
15 years 6 months ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang
BMCBI
2007
135views more  BMCBI 2007»
15 years 6 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...