Multivariate Statistics in Predictive Biotechnology

The aims of the studies are based on the main hypothesis that the combination of multivariate statistics and image analysis of features can be used as a tool in (visual and chemical) database identification processes within isolates from the fungal genera Penicillium and Aspergillus . Databases of functional characteristics are expected to be complementary to the known DNA-sequence based databases. The identification is based on visual as well as secondary metabolite profiles. Secondary metabolites are end products of the bio-chemical processes that take place within cells of all living organisms, and they are therefore indirectly descriptive of the cells metabolic processes. If different cells use different processes, there will also be a difference in the variety of metabolites produced. Furthermore the chemical variation in the metabolites can be directly related to ecology and habitat.