Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Mo...