DNA microarrays have considerably helped to improve the understanding of biological processes and diseases including multiple myeloma (MM). GEP analyses have been successful to classify MM, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance.This generated large amounts of publicly available data that could benefit from easy-to-use bioinformatics resources to analyze them. Here we present easy-to-use and open-access bioinformatics tools to extract and visualize the most prominent information from GEP data.
Keywords: Bioinformatics; Data mining; GenomicScape; Microarrays; Molecular heterogeneity; Multiple myeloma.