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IMSCCS
2006
IEEE
13 years 11 months ago
Clustering of Gene Expression Data: Performance and Similarity Analysis
Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
Longde Yin, Chun-Hsi Huang
BMCBI
2008
115views more  BMCBI 2008»
13 years 5 months ago
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung S...
BMCBI
2005
112views more  BMCBI 2005»
13 years 5 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
KDD
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 6 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
BMCBI
2008
142views more  BMCBI 2008»
13 years 5 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...