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Collectively coordinated cell migration plays a role in tissue embryogenesis,cancer, homeostasis and healing. To study these processes, different cell-basedmodelling approaches have been developed, ranging from lattice-based cellularautomata to lattice-free models that treat cells as point-like particles orextended detailed cell shape contours. In the spirit of what Osborne et al.[PLOS Computational Biology, (2017) 13, 1-34] did for cellular tissue structuresimulation models, we here compare five simulation models of collective cellmigration, chosen to be representative in increasing order of included detail.They are Vicsek-Gr\'egoire particles, Szab\'o-like particles, self-propelledVoronoi model, cellular Potts model, and multiparticle cells, where each modelincludes cell motility. We examine how these models compare when applied to thesame biological problem, and what differences in behaviour are due to differentmodel assumptions and abstractions. For that purpose, we use a benchmark thatdiscriminates between complex material flow models, and that can beexperimentally approached using cell cultures: the flow within a channel arounda circular obstacle, that is, the geometry Stokes used in his historical 1851experiment. For each model we explain how to best implement it; vary celldensity, attraction force and alignment interaction; draw the resulting maps ofvelocity, density and deformation fields; and eventually discuss its respectiveadvantages and limitations. We thus provide a recommendation on how to select amodel to answer a given question, and we examine whether models of motileparticles and motile cells display similar collective effects.

Discriminating between individual-based models of collective cell motion in a benchmark flow geometry using standardised spatiotemporal patterns