Research topics of the Section of Biosimulation and Bioinformatics are primarily related to objectives within the biosciences, aiming at the improvement of diagnostic and therapeutic procedures.

Starting from biomedical issues, specific models are derived and their behavior is tested by means of computer simulation ('computational modeling'). Simulation results are validated against experimental or clinical data (quality control). In contrast to real experiments, simulations can be repeatedly performed at arbitrary variation of input values and otherwise constant conditions. If simulation results compare satisfactorily with measurable data, the model may be assumed to produce reasonable results also for non-measurable quanitities.

Beside its value for (quanititative) description of functional relationships in biomedical systems, computational modeling has a potential to predict non-measurable processes or states of a system. Moreover, modeling may serve as a guideline for the analysis and interpretaion of measured data: If, for instance, the model shows a mechanism underlying the measurements (e.g. exponential decay), its parameters can be interpreted within the context of the system (e.g. as half-life time). In other words, formal fit parameters may turn into interpretable determinants of the system allowing forconclusions of biomedical relevance.

Modeling as well as analysis and interpretation of simulation results takes place in close cooperation with biomedical research groups. According to biomedical requirements, already established models and simulation methods may be modified, improved, or new ones developed. In turn, modeling and simulation techniques may thus add to the biomedical sciences in terms of newly available methodology.

On top of state-of-the-art skills in the computer sciences, modeling requires detailed education inbiological systems. In order to meet this claim, only a small number of issues (per person, per working group) can be effectively  pursued (focusing).