DNA analysis by microarrays is a powerful tool that allows replication of the RNA of hundreds of thousands of genes at the same time, generating a large amount of data in multidimensional space that must be analyzed using informatics tools. Various techniques have been applied to analyze the microarrays, but they do not offer a systematic form of analysis. This paper proposes the use of the Self- Organizing Maps (SOM) in an iterative way to find patterns of expressed genes. The new method proposed (Iterative Self-Organizing Maps, ISOM) has been evaluated with upregulated genes of the Escherichia Coli bacterium and is compared with the Self-Organizing Map (SOM) technique and a method which uses iteratively Gorban's Elastic Neural Net. In a comparative analysis of the three methods the ISOM shows the best results.