The mathematical description of organisms dates back to the beginning of the 20th century [1]. Since then, the theoretical understanding of biology has grown steadily, showing a more and more complex picture. With the emergence of computational models in physics, biophysicists started to adapt those models to describe biological processes [2]. An early development describing tissue development and cell–cell interactions was the so-called cellular Potts model (CPM) by Graner and Glazier ’92 [3]. This model derives from the Potts model and describes cells as connected areas on a grid. They were able to replicate known biological phenomena, such as adhesion driven cell sorting or tissue-growth. From then on, experimental insight into tissue on the cellular level as well as the power of computers has grown steadily, while the size and extent of cell-based tissue simulation have not proportionally evolved. Here, we present a modular framework for supercomputers to accommodate large-scale simulations of tissue with sub-single cell resolution.
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