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» Visualization methods for statistical analysis of microarray...
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131
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ICML
2006
IEEE
16 years 3 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
126
Voted
CIDM
2007
IEEE
15 years 8 months ago
Mining Subspace Correlations
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Rave Harpaz, Robert M. Haralick
115
Voted
BMCBI
2005
120views more  BMCBI 2005»
15 years 2 months ago
Harshlight: a "corrective make-up" program for microarray chips
Background: Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings...
Mayte Suárez-Fariñas, Maurizio Pelle...
151
Voted
CSDA
2007
264views more  CSDA 2007»
15 years 2 months ago
Model-based methods to identify multiple cluster structures in a data set
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Giuliano Galimberti, Gabriele Soffritti
164
Voted
BMCBI
2004
169views more  BMCBI 2004»
15 years 2 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...