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In these 3D environments, the mechanisms governing cell migration are far less understood due to both the technical challenges and the complexity of migratory behaviors (Zhu and Mogilner, 2016). doi: 10.1115/1.4032188 Pub Med Abstract | Cross Ref Full Text | Google Scholar Mark, C., Metzner, C., Lautscham, L., Strissel, P.

Based on the cell type and the cellular microenvironment (Te Boekhorst et al., 2016; Talkenberger et al., 2017)—in particular ECM parameters such as density, porosity and stiffness—, individual cells migrate using two distinct mechanisms (Friedl and Wolf, 2010; Swaney et al., 2010; Bear and Haugh, 2014).

Thus, cells are able to sense the spatial distribution of F. RES.0000259593.07661.1e Pub Med Abstract | Cross Ref Full Text | Google Scholar Lämmermann, T., Bader, B. J., Worbs, T., Wedlich-Söldner, R., Hirsch, K., et al. Rapid leukocyte migration by integrin-independent flowing and squeezing. doi: 10.1038/nature06887 Pub Med Abstract | Cross Ref Full Text | Google Scholar Li, T., Gu, Y.

This central connecting point—which can be associated to the cell nucleus or the cell centrosome—exists solely for modeling purposes as the point where all the bars are connected (Figure 1 right). Substrate stiffness regulates filopodial activities in lung cancer cells. doi: 10.1371/0089767 Pub Med Abstract | Cross Ref Full Text | Google Scholar Luster, A. Cellular migration plays a crucial role in many aspects of life and development. Fibroblast migration in 3D is controlled by haptotaxis in a non-muscle myosin II-dependent manner. In this paper, we propose a computational model of 3D migration that is solved by means of the tau-leaping algorithm and whose parameters have been calibrated using Bayesian optimization. doi: 10.1007/s40571-014-0017-4 Cross Ref Full Text | Google Scholar Moreno-Arotzena, O., Borau, C., Movilla, N., Vicente-Manzanares, M., and García-Aznar, J. The selection of an optimal parametrization is based on the balance between the defined evaluation metrics. Results show how the calibrated model is able to predict the main features observed in the in vitro experiments.