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.
Tools: Proteomics (2D-PAGE), qPCR, mutant strain generation, Northern analyses), Fluorecence based reporter gene analyses/single cell analyses, purification, molecular biological techniques (RNA/DNA techniques, enzymatic analyses, Protein chemical methods (protein overproduction, quantitative Western analyses)
I am research assistant in the microbiology department at the Ludwig-Maximilians Universität in Munich (München), working at the chair of Prof. Kirsten Jung. In our SysMO consortium we generate biological data and work in close cooperation with the workgroup of Dr. Andreas Kremling of the Max-Planck-Institut für Dynamik komplexer technischer Systeme in Magdeburg who performs mathematical modeling. The topic of our workpackage deals with "K+ homeostasis in Escherichia coli", wherby the K+ transporters,
Tools: including:- Dynamic modelling- Parameter estimation- Optimal experimental design- Dynamic optimization, Deterministic models, Computational Systems Biology, C programming, Stochastic models, enzymatic analyses, data modeling, linux, ODE, Computational and theoretical biology
Roles: Vice Coordinator
Expertise: enzyme kinetics, genome-scale modeling, Metabolic Pathway Analysis and Engineering Microbial Physiology Modeling of Biological Networks Industrial Systems Biotechnology White Biotech..., dynamics and control of biological networks
Since August 2008 I am professor in Systems Biology at the VU University Amsterdam. My Systems Bioinformatics group focusses on systems biology with a special focus on integrative bioinformatics. It aims at forming bridges between the classical bottom-up approaches in systems biology and the more data-driven approaches in classical bioinformatics. We combine experimental, modeling and theoretical approaches to study cellular physiology, with an emphasis on metabolic networks.