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Cellular Potts Model: Applications to Vasculogenesis and Angiogenesis

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Probabilistic Cellular Automata

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 27))

Abstract

The cellular Potts model (CPM, a.k.a. Glazier–Graner–Hogeweg or GGH model) is a somewhat liberal extension of probabilistic cellular automata. The model is derived from the Ising and Potts models and represents biological cells as domains of CA-sites of the same state. A Hamiltonian energy is used to describe the balance of forces that the biological cells apply onto one another and their local environment. A Metropolis algorithm iteratively copies the state from one site into one of the adjacent sites, thus shifting the domain interfaces and moving the biological cells along the lattice. The approach is commonly used in applications of developmental biology, where the CPM often interacts with systems of ordinary-differential equations that model the intracellular chemical kinetics and partial-differential equations that model the extracellular chemical signal dynamics to constitute a hybrid and multiscale description of the biological system. In this chapter we will introduce the cellular Potts model and discuss its use in developmental biology, focusing on the development of blood vessels, a process called vascular morphogenesis. We will start by introducing a range of models focusing on uncovering the basic mechanisms of vascular morphogenesis: network formation and sprouting and then show how these models are extended with models of intracellular regulation and with interactions with the extracellular micro-environment. We then briefly review the integration of models of vascular morphogenesis in several examples of organ development in health and disease, including development, cancer, and age-related macular degeneration. We end by discussing the computational efficiency of the CPM and the available strategies for the validation of CPM-based simulation models.

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Acknowledgements

We thank Indiana University and the Biocomplexity Institute for providing the CompuCell3D modeling environment and SURFsara (www.surfsara.nl) for the support in using the Lisa Compute Cluster. The investigations were in part supported by the Division for Earth and Life Sciences (ALW) with financial aid from the Netherlands Organization for Scientific Research (NWO) through Vidi grant 864.10.009. YJ was supported partially by the National Institute of Health grant U01CA143069.

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Authors and Affiliations

  1. Centrum Wiskunde & Informatica, Science Park 123, 1098 XG, Amsterdam, The Netherlands

    Sonja E. M. Boas, Roeland M. H. Merks & Elisabeth G. Rens

  2. Leiden University, Mathematical Institute, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Sonja E. M. Boas, Roeland M. H. Merks & Elisabeth G. Rens

  3. Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA

    Sotiris A. Prokopiou

  4. Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, 30303, USA

    Yi Jiang

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  1. Laboratoire de Mathématiques et Applications UMR 7348, Université de Poitiers, CNRS, Poitiers, France

    Pierre-Yves Louis

  2. University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Francesca R. Nardi

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Boas, S.E.M., Jiang, Y., Merks, R.M.H., Prokopiou, S.A., Rens, E.G. (2018). Cellular Potts Model: Applications to Vasculogenesis and Angiogenesis. In: Louis, PY., Nardi, F. (eds) Probabilistic Cellular Automata. Emergence, Complexity and Computation, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-65558-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-65558-1_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65556-7

  • Online ISBN: 978-3-319-65558-1

  • eBook Packages: EngineeringEngineering (R0)

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