Institutions: ZB MED - Information Centre for Life Scienceshttps://orcid.org/0000-0001-5246-9351
Projects: COVID-19 Disease Map
Institutions: University of Tübingenhttps://orcid.org/0000-0002-1240-5553
Expertise: Systems Biology, Computational Systems Biology, Databases, Dynamic modelling, Java, Mathematical modelling, Metabolic Engineering, Disease Maps, Curation, Modeling, Data Integration, Constraint-based Modelling, Parameter estimation
Andreas Dräger is the assistant professor for Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens at the University of Tübingen in Germany. His group aims to combat the spreading antibiotics resistances by using mathematical modeling and computer simulation of bacterial systems up to entire microbiomes and host-pathogen interactions. In doing so, his group actively contributes to the advancement of various COMBINE standards.
Tools: Biochemistry and protein analysis, Bioinformatics, Systems Biology, SBML, R, ODE, Molecular biology techniques (RNA/DNA/Protein), Genetics, Dynamic modelling, Computational and theoretical biology, CellDesigner, Parameter estimation
Institutions: University of Groningen
I work as a project manager for the Innovative Training Network PoLiMeR - Polymers in the LIver: Metabolism and Regulation funded by the EU. In addition I am a project manager for the UMCG Research BV where I support scientist in the pre-award phase with writing their proposals and in the post-award phase with managing their awarded projects.
Institutions: Institut Pasteurhttps://orcid.org/0000-0001-6286-1138
Institutions: National Institute of Biologyhttps://orcid.org/0000-0003-0913-2715
Projects: COMBINE Multicellular Modellinghttps://orcid.org/0000-0002-7692-7203
Institutions: Wageningen University & Researchhttps://orcid.org/0000-0001-7049-5334
I am a researcher (PhD student) working at Wageningen University & Research as bioinformatician and modeller. I am working as part of the MycoSynVac (http://www.mycosynvac.eu/) project on dynamic modelling of central carbon metabolism in M. pneumoniae, to be extended to full dynamic modelling of metabolism to be implemented in a whole cell model.
I am also looking into possibilities to improve standards in model generation using semantic technologies, improving automatic generation, annotation