Efficient Simulation of Cell-Biological Multi-Level Models (ESCeMMo)

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The number of more expressive languages that support a multi-level modeling and simulation is steadily growing in cell biology. Their rich features add to the flexibility and ease in modeling complex dynamic systems, but they also pose a challenge for efficient simulation. The aim of the research project ESCeMMo (Efficient Simulation of Cell-biological Multi-Level Models) is to develop more efficient execution strategies that take properties and requirements of expressive multi-level languages into account. As not all models will equally use the full set of features offered by expressive languages, tailored simulators that exploit specific constraints for more efficient simulation shall automatically be selected and applied. Multi-algorithm approaches shall be developed, which comprise an effective partitioning into sub-models, and the selection and synchronization of suitable simulators. Model decomposition as well as functional decomposition strategies shall be explored, for more effectively parallelizing single and multiple simulation runs. This research will be based on ML-Rules, an expressive rule-based language for multi-level modeling and simulation in cell biology. The developed methods will be evaluated by performance studies and a simulation study on mitochondria. The latter will also exploit central features of the modeling language. The results of the project will add to the efficiency of simulating multi-level models, enrich the portfolio of execution methods for expressive modeling languages, and will increase their applicability for answering cell biological research questions.