The work related to DA-BiMaSc covers two different fields of application: biology and material sciences. Both fields share the same nature of the fundamental data, e. g. spectra, depth profiles, or numerical matrices. Applied methods come from statistics, artificial intelligence, and computational intelligence. Objective of the work is the detection of relationships between the fundamental data and biological or physical properties.
Novel high-tech materials are based on new alloys, new production techniques, or new coating types. One objective is the increase of corrosion resistance, without impairing other technical properties such as paint adhesion, formability and scratch resistance. There is a need to be able to characterise these new types of materials with both fast andbanalytically comprehensive techniques. The characterisation is mainly based on the following analytical measuring technologies:
The evaluation of the fundamental data is based on statistical methods, as well as methods coming from the field of artificial and computational intelligence. Applied methods are
Biological sciences such as Genomics, Proteomics and Metabolomics aim at understanding the principles and mechanisms of living cells and organisms on microscopic and molecular level. Experimental data is produced in both qualitative and quantitative manner and contain both already known and yet unknown dependencies or correlations within or between genes and
metabolites. Following technologies are used:
Statistical and computational methods for the analysis and identification of global and local correlation and dependencies within the data are designed, based on