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Yuriria Cortes-Poza

Publications and source records attributed to Yuriria Cortes-Poza.

2 recordsLinked to original sources

New links between PDE's and Voronoi patterns

This paper presents a range of results in partial differential equations (PDEs) in which Voronoi patterns arise. We investigate the connection between the solution to an elliptic equation and its probabilistic interpretation as a stochastic colonization game. An agent-based model is designed and implemented to generate the Voronoi cells simulating experimental results with bacteria. We also consider the analytical solution to the problem, which enables us to define what we call a harmonic Voronoi tessellation. We analyze parabolic equations in Riemannian manifolds, which have important applications in chemical reactions and diffusive fronts. By utilizing short-time heat kernel estimates, we demonstrate that the interaction of $n$ point sources gives rise to a Voronoi tessellation. We recall some well-known results of wavefronts interactions from point light sources and the Huygens principle. We apply results about the particular set of weak solutions to the eikonal equation to characterize Voronoi patterns arising in this context as rectifiable sets. Finally, we present an optimal transport problem and the corresponding Monge-Ampère equation, in which a uniform measure is transported to a sum of $n$ Dirac masses with a cost given by the Euclidean distance. These problems are naturally linked to power sets, a generalization of Voronoi tessellations.

math.AP

Forest structure in epigenetic landscapes

Morphogenesis is the biological process that causes the emergence and changes of patterns (tissues and organs) in living organisms. It is a robust, self-organising mechanism, governed by Genetic Regulatory Networks (GRN), that hasn't been thoroughly understood. In this work we propose Epigenetic Forests as a tool to study morphogenesis and to extract valuable information from GRN. Our method unfolds the richness and structure within the GRN. As a case study, we analyze the GRN during cell fate determination during the early stages of development of the flower Arabidopsis thaliana and its spatial dynamics. By using a genetic algorithm we optimize cell differentiation in our model and correctly recover the architecture of the flower.

q-bio.MN