Systems Biology & Metabolοmiсs

Profile: Systems Biology and Metabolomics

C: The programme focuses on the reprogramming mechanisms of the metabolism in association with phenotypic, physiological or behavioural changes including disease development. Current techniques of Metabolomics and Bioanalytics including quantitative metabolite analysis methods (chromatography, mass spectrometry) are applied for comprehensive gene function- or stress response analyses. Both bioinformatics and complex computational approaches give insights into the field of computational biology. 

In particular, advances and current results of bioinformatics including genome and sequence analysis, protein domains or protein families, large-scale data analysis (e.g. next generation sequences, proteomics data), analysis of different functional RNAs (e.g. miRNAs, lncRNAs) are explained and discussed. Furthermore, aspects of functional genomics, the dynamics of either the transcriptome or of metabolism and metabolic networks up to regulatory networks are illustrated.

The two major topics are composed of two theory modules as well as a practical course unit each. Further research training is provided in a selected field of interest, and the students are actively involved in ongoing research projects and learn to independently plan and perform both theoretical and experimental work and finally, to summarize and discuss the results obtained in the thesis.  

Objectives and Learning Outcomes

The students become familiar with state of the art approaches to comprehensively analyze physiological changes using current techniques of Metabolomics and Bioanalytics. They are trained to understand recent results in systems biology and to discuss corresponding implications. The students become familiar with theoretical aspects and principles in comprehensive bioanalytical approaches in cell biology, developmental biology, microbiology.  They experience the complex interactions of living organisms including the importance of time and place to result in successful reproduction or synergy.  With several bioinformatics tools, they are able to use computational biology based approaches to address and resolve problems in selected bioscientific fields.