2009/01/01 by Sonja Mathias, Adrien Coulier, Anass Bouchnita +2 · 2 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Social Sciences · #Applied mathematics #Art #Artificial intelligence #Biology #Cell #Cellular Mechanics and Interactions #Comparative and International Law Studies #Computational model #Computer science #Computer simulation #Function (biology) #Gene Regulatory Network Analysis #Mathematical Biology Tumor Growth #Mathematical optimization #Mathematics #Multicellular organism #Pairwise comparison #Population #Robustness (evolution) #Simulation
paper · pdf · open access · doi:10.1007/s11538-020-00810-2
published in Nature Today 2009(10), 132 (Naturalis Biodiversity Center)
openalex publication_date 2009/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Centre-based or cell-centre models are a framework for the computational study of multicellular systems with widespread use in cancer modelling and computational developmental biology. At the core of these models are the numerical method used to update cell positions and the force functions that encode the pairwise mechanical interactions of cells. For the latter, there are multiple choices that could potentially affect both the biological behaviour captured, and the robustness and efficiency of simulation. For example, available open-source software implementations of centre-based models rely on different force functions for their default behaviour and it is not straightforward for a modeller to know if these are interchangeable. Our study addresses this problem and contributes to the understanding of the potential and limitations of three popular force functions from a numerical perspective. We show empirically that choosing the force parameters such that the relaxation time for two cells after cell division is consistent between different force functions results in good agreement of the population radius of a two-dimensional monolayer relaxing mechanically after intense cell proliferation. Furthermore, we report that numerical stability is not sufficient to prevent unphysical cell trajectories following cell division, and consequently, that too large time steps can cause geometrical differences at the population level.