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.
SEEK ID: https://fairdomhub.org/people/445
Expertise: Image processing, Image analysis, Dynamic Systems, Data analysis, Identifiability, parameter estimation, Systems Biology, Cellular Senescence, Signalling networks, Databases, Model selection, Cell Cycle, dynamics of biological networks.
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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
Authors: J. Schaber, A. Lapytsko, D. Flockerzi
Date Published: No date defined
Journal: J R Soc Interface
PubMed ID: 24307567
Citation: J R Soc Interface. 2013 Dec 4;11(91):20130971. doi: 10.1098/rsif.2013.0971. Print 2014 Feb 6.
Date Published: 12th Jul 2017
Journal: PLoS One
PubMed ID: 28692669
Citation: PLoS One. 2017 Jul 10;12(7):e0180331. doi: 10.1371/journal.pone.0180331. eCollection 2017.
Authors: J. Schaber, R. Baltanas, A. Bush, E. Klipp, A. Colman-Lerner
Date Published: 15th Nov 2012
Journal: Mol Syst Biol
PubMed ID: 23149687
Citation: Mol Syst Biol. 2012;8:622. doi: 10.1038/msb.2012.53.