Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of ...
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: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Efficient and effective analysis of large datasets from microarray gene expression data is one of the keys to time-critical personalized medicine. The issue we address here is the ...