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BMCBI
2004
87views more  BMCBI 2004»
13 years 4 months ago
Selection of informative clusters from hierarchical cluster tree with gene classes
Background: A common clustering method in the analysis of gene expression data has been hierarchical clustering. Usually the analysis involves selection of clusters by cutting the...
Petri Törönen
BMCBI
2010
153views more  BMCBI 2010»
13 years 5 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
181views more  BMCBI 2004»
13 years 4 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
JCB
2002
160views more  JCB 2002»
13 years 4 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
BMCBI
2007
173views more  BMCBI 2007»
13 years 4 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...