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1.
J Biol Dyn ; 9 Suppl 1: 104-27, 2015.
Article in English | MEDLINE | ID: mdl-25186246

ABSTRACT

Birth-jump models are designed to describe population models for which growth and spatial spread cannot be decoupled. A birth-jump model is a nonlinear integro-differential equation. We present two different derivations of this equation, one based on a random walk approach and the other based on a two-compartmental reaction-diffusion model. In the case that the redistribution kernels are highly concentrated, we show that the integro-differential equation can be approximated by a reaction-diffusion equation, in which the proliferation rate contributes to both the diffusion term and the reaction term. We completely solve the corresponding critical domain size problem and the minimal wave speed problem. Birth-jump models can be applied in many areas in mathematical biology. We highlight an application of our results in the context of forest fire spread through spotting. We show that spotting increases the invasion speed of a forest fire front.


Subject(s)
Fires , Forests , Models, Biological , Diffusion , Population Dynamics
2.
IET Syst Biol ; 6(4): 143-53, 2012 Aug.
Article in English | MEDLINE | ID: mdl-23039695

ABSTRACT

Many spatial patterns in biology arise through differentiation of selected cells within a tissue, which is regulated by a genetic network. This is specified by its structure, parameterisation and the noise on its components and reactions. The latter, in particular, is not well examined because it is rather difficult to trace. The authors use suitable local mathematical measures based on the Voronoi diagram of experimentally determined positions of epidermal plant hairs (trichomes) to examine the variability or noise in pattern formation. Although trichome initiation is a highly regulated process, the authors show that the experimentally observed trichome pattern is substantially disturbed by cell-to-cell variations. Using computer simulations, they find that the rates concerning the availability of the protein complex that triggers trichome formation plays a significant role in noise-induced variations of the pattern. The focus on the effects of cell noise yields further insights into pattern formation of trichomes. The authors expect that similar strategies can contribute to the understanding of other differentiation processes by elucidating the role of naturally occurring fluctuations in the concentration of cellular components or their properties.


Subject(s)
Arabidopsis/anatomy & histology , Arabidopsis/growth & development , Models, Biological , Models, Statistical , Plant Cells/physiology , Plant Cells/ultrastructure , Plant Development/physiology , Cell Enlargement , Cell Proliferation , Computer Simulation , Models, Anatomic
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