The Next Generation Computer Systems Group (SING) brings together a reduced number of researches with the aim of developing intelligent models and deploying them in real environments. The expertise of the members comes from different areas related with previous research in developing symbolic, connexionistic and hybrid AI systems, solving security problems, administration of networks, e-commerce, VoIP, implementation of web applications and developing systems working with documental data bases. The projects carried out by the SING group always follow a practical point of view, but taking into consideration the formal aspects needed in any research work. Indeed, most interesting techniques employed in previous works cope with the utilisation of case-based reasoning, artificial neural networks, fuzzy logic, rough sets, intelligent agents and multi-agent systems.
Understanding the molecular basis of phenotypic variation is one of the main aims of Biological and Biomedical sciences. Nevertheless most phenotypic traits of interest are influenced by variation at multiple genes, and this is likely the main reason why such knowledge is available for a few traits and species only. The diverse but complementary expertise of the members of the Phenotypic Evolution group, ranging from bioinformatics (including software development), genomics, proteomics, statistics, evolution, structural biology, biophysics, biochemistry, and molecular biology means that it is possible to tackle such a difficult problem from an integrated point of view, thus, increasing the chances of success. Such diverse know-how is the result of the integration of researchers from 3 different IBMC research groups (Molecular Evolution, Evolutionary Systems Biology and Protein Crystallography).