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KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 8 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
ITA
2006
167views Communications» more  ITA 2006»
13 years 7 months ago
Characterization of lung tumor subtypes through gene expression cluster validity assessment
The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at b...
Giorgio Valentini, Francesca Ruffino
BMCBI
2008
178views more  BMCBI 2008»
13 years 7 months ago
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
BMCBI
2004
206views more  BMCBI 2004»
13 years 7 months ago
Combining gene expression data from different generations of oligonucleotide arrays
Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public re...
Kyu Baek Hwang, Sek Won Kong, Steven A. Greenberg,...