In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
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...
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...