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» Clustering gene expression patterns
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BMCBI
2004
181views more  BMCBI 2004»
14 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
2008
160views more  BMCBI 2008»
14 years 10 months ago
A comparison of four clustering methods for brain expression microarray data
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
BMCBI
2006
152views more  BMCBI 2006»
14 years 9 months ago
Amplification of the Gene Ontology annotation of Affymetrix probe sets
Background: The annotations of Affymetrix DNA microarray probe sets with Gene Ontology terms are carefully selected for correctness. This results in very accurate but incomplete a...
Enrique M. Muro, Carolina Perez-Iratxeta, Miguel A...
BMCBI
2006
120views more  BMCBI 2006»
14 years 9 months ago
An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
Ryung S. Kim, Hongkai Ji, Wing Hung Wong
AI
2006
Springer
15 years 1 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda