Endothelial cells, which build a barrier between blood and tissue, are permanently exposed to fluid shear stress that has a tremendous impact on endothelial functions. In order to get a better understanding of the behaviour of endothelial cells under shear stress, we conduct a large number of experiments using our BTF ("BioTechFlow") system. Particularly the continuous determination of the endothelial barrier function and the time lapse recording to analyze cell morphology and migration generate an immense number of data sets that have to be analyzed in a local as well as a global way. Up to now, data have been stored in hundreds of separate files, resulting in tedious manual work when performing model-based analysis steps. In our project, we exploit the benefit of implementing an experimental management and analysis infrastructure with a central database. First of all, the analysis task comprises the step of gathering experimental raw data directly into the database. The second step-which heavily exploits functionality of the underlying database system-applies mathematical models, e.g. curve fitting algorithms, to yield a more abstract representation of the very specific experiment. The third step finally conducts comparative statistical methods to detect, for example correlations in the derived data. Overall, our infrastructure provides a way to centrally organize many data sets and to perform comprehensive analysis methods including data mining.