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BMCBI
2006
213views more  BMCBI 2006»
13 years 9 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 10 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
BMCBI
2004
181views more  BMCBI 2004»
13 years 9 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BMCBI
2006
136views more  BMCBI 2006»
13 years 9 months ago
Metric for Measuring the Effectiveness of Clustering of DNA Microarray Expression
Background: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultane...
Raja Loganantharaj, Satish Cheepala, John Clifford
KDD
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 9 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,...