In contrast to DNA, RNA prevails as a single strand. As a consequence of small self-complementary regions, RNA commonly exhibits an intricate secondary structure, consisting of relatively short, double helical segments alternated with single stranded regions. The amount of sequence data available is rising rapidly day by day. One of the problems encountered on a specific molecule is finding the relevant data between the massive number of other sequences to be done by reading lists with a short description of all new entries in large databases already existing. One of the main objectives of this work is to take the extracted structures of aligned ribosomal RNA sequences and their secondary structures and cluster them. The proposal is to apply existing dimensionality reduction algorithms to these extracted structures and then cluster them in a reduced dimensional space using Support Vector Machines.