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BMCBI
2008
122views more  BMCBI 2008»
13 years 9 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
117views more  BMCBI 2007»
13 years 9 months ago
Meta-analysis of several gene lists for distinct types of cancer: A simple way to reveal common prognostic markers
Background: Although prognostic biomarkers specific for particular cancers have been discovered, microarray analysis of gene expression profiles, supported by integrative analysis...
Xinan Yang, Xiao Sun
JMM2
2008
124views more  JMM2 2008»
13 years 8 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
PR
2006
116views more  PR 2006»
13 years 8 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli
BMCBI
2008
129views more  BMCBI 2008»
13 years 9 months ago
EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management
Background: Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large d...
Geraint Barton, J. C. Abbott, Norie Chiba, D. W. H...