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2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2017)
Kansas City, MO, USA
Nov. 13, 2017 to Nov. 16, 2017
ISBN: 978-1-5090-3051-4
pp: 556-60
Cheikhou Oumar Ka , Laboratoire d'Analyse Numérique et d'Informatique, BP 234, Université Gaston Berger, Saint-Louis, Sénégal
Jean-Marie Dembele , Laboratoire d'Analyse Numérique et d'Informatique, BP 234, Université Gaston Berger, Saint-Louis, Sénégal
Christophe Cambier , IRD, Sorbonne Universités, UPMC Univ Paris 06, UMI 209 UMMISCO, 32 Avenue Henri Varagnat, 93143 Bondy Cedex, France
Serge Stinckwich , IRD, Sorbonne Universités, UPMC Univ Paris 06, UMI 209 UMMISCO, 32 Avenue Henri Varagnat, 93143 Bondy Cedex, France
Moussa Lo , Laboratoire d'Analyse Numérique et d'Informatique, BP 234, Université Gaston Berger, Saint-Louis, Sénégal
Jean-Daniel Zucker , IRD, Sorbonne Universités, UPMC Univ Paris 06, UMI 209 UMMISCO, 32 Avenue Henri Varagnat, 93143 Bondy Cedex, France
ABSTRACT
To investigate cell spatial organization in complex biological dynamics, an individual-based model that represents cell motion in a deterministic way is proposed and then experimented on avascular tumor growth case. Cell motion remains a fundamental process in many complex biological dynamics such as morphogenesis or cell aggregation. Mathematical models are often used to represent cellular motility and spatial dynamics. However, the variability and the interactions between individuals, which are crucial to build accurate predictive models, are difficult to represent using differential equations. We propose, in this paper, an individual-based approach that allows describing cell motion at deterministic way with diffusion and convection processes. Such approach is built using Smoothed Particle Hydrodynamics (SPH) method and allows representing spatially each cell and its basic biological primitives. The relevance of this approach is illustrated on avascular tumor growth to study the effects of microenvironment (nutrients) and cell individual motion in tumor development. The results shown that the model can qualitatively predict a number of cellular behaviors that have been observed in experiments.
INDEX TERMS
Mathematical model, Tumors, Convection, Biological system modeling, Sugar, Organizations
CITATION

C. O. Ka, J. Dembele, C. Cambier, S. Stinckwich, M. Lo and J. Zucker, "Deterministic convection-diffusion approach for modeling cell motion and spatial organization: Experimentation on avascular tumor growth," 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, USA, 2017, pp. 556-60.
doi:10.1109/BIBM.2017.8217709
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