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Particle simulations of morphogenesis


Koumoutsakos, P; Bayati, B; Milde, F; Tauriello, G (2011). Particle simulations of morphogenesis. Mathematical Models and Methods in Applied Sciences, 21(Supp. 1):955-1006.

Abstract

The simulation of the creation and evolution of biological forms requires the development of computational methods that are capable of resolving their hierarchical, spatial and temporal complexity. Computations based on interacting particles, provide a unique computational tool for discrete and continuous descriptions of morphogenesis of systems ranging from the molecular to the organismal level. The capabilities of particle methods hinge on the simplicity of their formulation which enables the formulation of a unifying computational framework encompassing deterministic and stochastic models. In this paper, we discuss recent advances in particle methods for the simulation of biological systems at the mesoscopic and the macroscale level. We present results from applications of particle methods including reaction diffusion on deforming surfaces, deterministic and stochastic descriptions of tumor growth and angiogenesis and discuss successes and challenges of this approach.

Abstract

The simulation of the creation and evolution of biological forms requires the development of computational methods that are capable of resolving their hierarchical, spatial and temporal complexity. Computations based on interacting particles, provide a unique computational tool for discrete and continuous descriptions of morphogenesis of systems ranging from the molecular to the organismal level. The capabilities of particle methods hinge on the simplicity of their formulation which enables the formulation of a unifying computational framework encompassing deterministic and stochastic models. In this paper, we discuss recent advances in particle methods for the simulation of biological systems at the mesoscopic and the macroscale level. We present results from applications of particle methods including reaction diffusion on deforming surfaces, deterministic and stochastic descriptions of tumor growth and angiogenesis and discuss successes and challenges of this approach.

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Additional indexing

Item Type:Journal Article, not refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > WingX
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2011
Deposited On:11 Jul 2013 10:46
Last Modified:07 Dec 2017 21:39
Publisher:World Scientific Publishing
ISSN:0218-2025
Additional Information:Electronic version of an article published as Journal Mathematical Models and Methods in Applied Sciences, Volume 21, Supp. 1, 2011 Article DOI 10.1142/S021820251100543X
Publisher DOI:https://doi.org/10.1142/S021820251100543X

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