Intelligent system for the analysis of microarray data using principal components and estimation of distribution algorithms

摘要

BackgroundMicroarray technology allows to measure the expression of thousands of genes simultaneously, and under tens of specific conditions. Clustering and Biclustering are the main tools to analyze gene expression data obtained from microarray experiments. By grouping together genes with the same behavior across samples, relevant biological knowledge may be extracted. Non-exclusive groupings are required, since a gene may play more than one biological role. Gene Shaving [Hastie, T., et al. (2000). Gene Shaving as a method for identifying distinct sets of genes with similar expression. Genome Biology, 1, 1–21] is a popular clustering algorithm which looks for coherent clusters of genes with high variance across samples, allowing overlapping among the clusters.