We develop two models for Myxobacteria swarming, a modified Lattice Gas Cellular Automata (LGCA) model and an off-lattice CA model. In the LGCA model each cell is represented by one node for the center of mass and an extended rod-shaped cell profile. Cells check the surrounding area and choose in which direction to move based on the local interactions. Using this model, we obtained a density vs. expansion rate curve with the shape similar to the experimental curve for the wild type Myxobacteria. In the off-lattice model, each cell is represented by a string of nodes. Cells can bend and move freely in the two-dimensional space. We use a phenomenological algorithm to determine the moving direction of cells guided by slime trail; the model allows for cell bending and alignment during collisions. In the swarming simulations for A+S-Myxobacteria, we demonstrate the formation of peninsula structures, in agreement with experiments. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wu, Y., Chen, N., Rissler, M., Jiang, Y., Kaiser, D., & Alber, M. (2006). CA models of myxobacteria swarming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4173 LNCS, pp. 192–203). Springer Verlag. https://doi.org/10.1007/11861201_24
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