Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...
Abstract-- Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (i...
Most of the biclustering algorithms for gene expression data are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However...
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...