Genome-scale metabolic network modeling has become one of the most successful approaches in systems biology to investigate cellular metabolism. The work typically consists of two phases: (1) de novo reconstruction or refinement of a genome-scale metabolic network, and (2) analysis of the resulting network using constraint-based computational modelling. Flux Balance Analysis (FBA) is the most basic constraint-based approach and is founded on a few simple assumptions in connection with linear programming.
In our work, we build genome-scale network reconstructions and develop a variety of mathematical and computational approaches for identifying basic properties and engineering strategies. Realizing that a crucial component of genome-scale metabolic reconstructions, the so-called Biomass reaction, quite often is based on guesswork and analogies between organisms, we have now initiated a large-scale initiative involving several research groups at Dept. of Biotechnology to conduct high-quality experimental determination of cellular composition to be used in these models.