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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2010
151views more  BMCBI 2010»
15 years 1 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
DIS
2006
Springer
15 years 5 months ago
On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets
Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algori...
Ata Kabán, Jianyong Sun, Somak Raychaudhury...
104
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BMCBI
2005
126views more  BMCBI 2005»
15 years 1 months ago
An algorithm for automatic evaluation of the spot quality in two-color DNA microarray experiments
Background: Although DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experiment...
Eugene Novikov, Emmanuel Barillot
BMCBI
2008
169views more  BMCBI 2008»
15 years 1 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
BMCBI
2010
118views more  BMCBI 2010»
15 years 1 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...