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...
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...
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...
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,...
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...