Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
Background: The hierarchical clustering tree (HCT) with a dendrogram [1] and the singular value decomposition (SVD) with a dimension-reduced representative map [2] are popular met...
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...