Mass Spectrometry and Molecular Analysis

Data management, data interpretation and structure analysis

Integrated course, 4.00 ECTS


Course content

Biological data management and knowledge management systems, data base structure and data formats, procedures of exploratory data analysis, normalization procedures and data reduction, data and structure analysis with multivariate statistical approaches (principal component analysis (PCA), independent component analysis (ICA), PLS discriminant analysis (PLS-DA), cluster analysis.

Learning outcomes

The students are able to use purposeful tools of bioinformatics in the required situation. This includes the suitable choice and handling of primary and secondary internet databases like RNA and DNA databases, protein sequence databases, microarray databases, protein interaction data bases, and structure databases. The students are familiar with the most relevant web portals with regard to the access to the databases and relevant tools for data manipulation (NCBI, ExPASy, KEGG). In addition, they can handle tools to analyze sequences of nucleic acids and proteins (e.g. fasta, blast, etc.) and can interpret the obtained results. In the field of statistical procedures the students are able to prepare experimental data (standardization and transformation algorithms) and can analyze them in various statistical tests and can interpret the results. They are familiar with multivariate statistical methods to interpret complex relationships and to recognize significant changes of command variables in the field of applied OMICS technologies. This includes the main component analysis (PCA) and the PLS discrimination analysis (PLS-DA). In the validation process of analytical methods they know the fundamental norm ISO/IEC 17025 and they are able to explain characteristic features of analytical methods.