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Microarray approaches are widely used high-throughput techniques to assess simultaneously the expression of thousands of genes under certain conditions and study the effects of certain treatments, diseases, and developmental stages. The traditional way to perform such experiments is to design oligonucleotide hybridization probes that correspond to specific genes and then measure the expression of the genes in order to determine which of them are up- or down-regulated compared to a condition that is used as a control. Hitherto, individual experiments cannot capture the bigger picture of how a biological system works and, therefore, data integration from multiple experimental studies and external data repositories is necessary to understand the function of genes and their expression patterns under certain conditions. Therefore, the development of methods for handling, integrating, comparing …