The creation of models for heterogeneous and complex cellular networks is a central goal of Systems Biology. When modeling a biological network, one may wish to account for certain aspects in detail, while a bird's eye perspective would seem more appropriate for other parts. Multi-level models combine such overview and detail representations. Descriptions at different temporal scales allow to model both slow and fast sub-systems of a dynamic system within one model. Descriptions at different abstraction levels are supported by the composition of models, and by variables that scale over various orders of magnitude. Compositions allow to structure according to function and to distinguish between individuals. When quantitative variables are transformed into qualitative ones, certain ranges of values are aggregated. Descriptions at micro and macro level capture the dynamics of interacting individuals as well as that of entire populations. Thus, the macro level forms also an aggregation, i.e. an aggregation of models representing individuals all belonging to the same population. The more complex biological systems become the more a multi-level approach towards their modeling and simulation is required. Therefore some research into the possibilities and limitations of existing modeling and simulation methods to support such multiple perceptions on biological systems is overdue. The goal of the project is to develop new methods addressing the particular challenges of multi-level models in Systems Biology. This can only be achieved based on concrete applications and in close cooperation with wet-lab partners.