Internal Impressum Sitemap
 
IMC
ZIH
TU Dresden
Dept. for Innovative
Methods of Computing
 

Cellular Automata

Cellular automata are discrete dynamical systems. They were introduced by J. von Neumann and S. Ulam in the 1950s in an attempt to model biological self-reproduction. Since then, it has become clear that CA have a much broader potential as models for physical, chemical and biological self-organization. We develop cellular automata and other cell-based models (e.g. cellular Potts model) for studying the emergence of collective behavior emerging from the interaction of individual components, such as molecules, cells or organisms.

Simulation results of cellular automaton model.

Cellular automaton modelling of collective and single-cell dynamics in dependence of cell–cell adhesion and extracellular confinement (from: O. Ilina, ...S. Syga, J. Starruß, A. Deutsch, P. Friedl, Cell–cell adhesion and 3D matrix confinement determine jamming transitions in breast cancer invasion, Nature Cell Biology 22, 1103–1115, 2020).

Cooperations:

Dr. Nazim Fates (INRIA Nancy, France)
Prof. Niloy Ganguly (Department of Computer Science and Engineering, Kharagpur, India)
Prof. Dr. Dieter Wolf-Gladrow (Alfred Wegener Institute, Bremerhaven)

Key Publications:

  • H. Hatzikirou, G. Breier, A. Deutsch
    Cellular Automaton Modeling of Tumor Invasion
    Encyclopedia of Complexity and Systems Science (Ed. R. A. Meyers, Springer Berlin), 1-13, 2020 [DOI]

  • S. Syga, J. M. Nava-Sedeño, L. Brusch, A. Deutsch
    A Lattice-Gas Cellular Automaton Model for Discrete Excitable Media
    in Spirals and Vortices, Müller and Tsuji(Eds.), Chapter - 15, 253-264, Springer, 2019 [DOI]

  • J. M. Nava-Sedeño, H. Hatzikirou, R. Klages, A. Deutsch
    Cellular automaton models for time-correlated random walks: derivation and analysis
    Scientific Reports, 7, 1, 16952, 2017 [DOI]

  • J. M. Nava-Sedeno, H. Hatzikirou, F. Peruani, A. Deutsch
    Extracting cellular automaton rules from physical Langevin equation models for single and collective cell migration
    J. Math. Biol., 75, 5, 1075-1100, 2017 [DOI]

  • A. Deutsch
    Cellular automaton models for collective cell behaviour
    Lecture Notes in Computer Science, 9099, 1-10, 2015 [DOI]

  • C. Mente, A. Voss-Böhme, A. Deutsch
    Analysis of Individual Cell Trajectories in Lattice-Gas Cellular Automaton Models for Migrating Cell Populations
    Bulletin of Mathematical Biology, 77, 4, 1-38, 2015 [DOI]

  • H. Hatzikirou, A. Deutsch
    Lattice-gas cellular automaton modeling of emergent behavior in interacting cell populations
    In: Simulating Complex Systems by Cellular Automata
    301-331, 2010 [DOI]

  • H. Hatzikirou, L. Brusch, A. Deutsch
    From cellular automaton rules to an effective macroscopic mean-field description
    Acta Physica Polonica B Proceedings Supplement, 3, 399-416, 2010 [PDF]

  • Book: Cellular Automaton Modeling of Biological Pattern Formation: Characterization, Applications, and Analysis
    A. Deutsch, S. Dormann
    Birkhäuser, Boston, 2017 (2nd ed.)
    Springer
logos