We develop various mathematical approaches to analyze cellular networks. One particular focus is theoretical and compu­ta­tio­nal methods for modeling and targeted modification of metabolic networks. We are also interested in mathematical modelling of microbial communities.

We combine computational (dry-lab) and genetic (wet-lab) techniques to test and establish new metabolic engineering strategies to develop microbial cell factories for the bio-based production of chemicals. As relevant host organism we focus on E. coli and, more recently, also on yeast (S. cerevisiae).

We use systems biology methods and various experimental techniques to elucidate metabolic and regulatory processes in E. coli which are often also crucial for biotechnological applications (e.g., adaptation to changing nutrient and oxygen concentrations).

Genes and proteins of regulatory and signaling networks are often known whereas many of their mutual interactions remain still undiscovered or are unclear. Our group develops and applies novel algorithms for the computer-aided identification of cellular signaling and gene regulatory networks from experimental data.

We continually develop (and maintain) CellNetAnalyzer, a comprehensive MATLAB toolbox for the mathematical modeling and analysis of biological networks. CellNetAnalyzer is part of de.NBI and we offer extended user services including web tutorials and training workshops.