Web page: http://www.ovgu.de/
Expertise: Image processing, Image analysis, Dynamic Systems, Signalling networks, dynamics of biological networks., parameter estimation, Databases, Data analysis, Systems Biology, Model selection, Identifiability, Cellular Senescence, Cell Cycle
My group investigates dynamic regulation and control mechanisms of cellular signal transduction networks by a combination of theoretical, experimental and computational methods. We seek to make sense of our biological data with the help of mathematical models, which ideally enable us to make valid predictions for new experiments, thereby generating novel biological insights.
Microbial strains used in biotechnological industry need to produce their biotechnological products at high yield and at the same time they are desired to be robust to the intrinsic nutrient dynamics of large-scale bioreactors, most noticeably to transient limitations of carbon sources and oxygen. The engineering principles for robustness of metabolism to nutrient dynamics are however not yet well understood. The ROBUSTYEAST project aims to reveal these principles for microbial strain improvement
Within the e:Bio - Innovationswettbewerb Systembiologie (Federal Ministry of Education and Research (BMBF)), the SulfoSYSBIOTECH consortium (10 partners), aim to unravel the complexity and regulation of the carbon metabolic network of the thermoacidophilic archaeon Sulfolobus solfataricus (optimal growth at 80°C and pH 3) in order to provide new catalysts ‘extremozymes’ for utilization in White Biotechnology.
Based on the available S. solfataricus genome scale metabolic model (Ulas et al., 2012)
Systems Biology studies the properties and phenotypes that emerge from the interaction of biomolecules where such properties are not obvious from those of the individual molecules. By connecting fields such as genomics, proteomics, bioinformatics, mathematics, cell biology, genetics, mathematics, engineering and computer sciences, Systems Biology enables discovery of yet unknown principles underlying the functioning of living cells. At the same time, testable and predictive models of complex