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BMCBI
2005
112views more  BMCBI 2005»
13 years 8 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...
AIME
2007
Springer
14 years 3 months ago
Interpreting Gene Expression Data by Searching for Enriched Gene Sets
This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment o...
Igor Trajkovski, Nada Lavrac
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 9 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
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,...
BMCBI
2006
109views more  BMCBI 2006»
13 years 8 months ago
Integrated analysis of gene expression by association rules discovery
Background: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditi...
Pedro Carmona-Saez, Monica Chagoyen, Andrés...