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» Evaluation of clustering algorithms for gene expression data
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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, ...
IJPP
2008
158views more  IJPP 2008»
13 years 4 months ago
The ParTriCluster Algorithm for Gene Expression Analysis
Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under...
Renata Braga Araújo, Guilherme Henrique Tri...
BMCBI
2008
259views more  BMCBI 2008»
13 years 5 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....
RECOMB
2006
Springer
14 years 5 months ago
Identification and Evaluation of Functional Modules in Gene Co-expression Networks
Abstract. Identifying gene functional modules is an important step towards elucidating gene functions at a global scale. In this paper, we introduce a simple method to construct ge...
Jianhua Ruan, Weixiong Zhang