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Stochastic simulation algorithms for Interacting Particle Systems.
Stutz, Timothy C; Landeros, Alfonso; Xu, Jason; Sinsheimer, Janet S; Sehl, Mary; Lange, Kenneth.
Afiliação
  • Stutz TC; Department of Computational Medicine, University of California, Los Angeles, CA, United States of America.
  • Landeros A; Department of Computational Medicine, University of California, Los Angeles, CA, United States of America.
  • Xu J; Department of Statistical Sciences, Duke University, Durham, NC, United States of America.
  • Sinsheimer JS; Department of Computational Medicine, University of California, Los Angeles, CA, United States of America.
  • Sehl M; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, United States of America.
  • Lange K; Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, United States of America.
PLoS One ; 16(3): e0247046, 2021.
Article em En | MEDLINE | ID: mdl-33651796
ABSTRACT
Interacting Particle Systems (IPSs) are used to model spatio-temporal stochastic systems in many disparate areas of science. We design an algorithmic framework that reduces IPS simulation to simulation of well-mixed Chemical Reaction Networks (CRNs). This framework minimizes the number of associated reaction channels and decouples the computational cost of the simulations from the size of the lattice. Decoupling allows our software to make use of a wide class of techniques typically reserved for well-mixed CRNs. We implement the direct stochastic simulation algorithm in the open source programming language Julia. We also apply our algorithms to several complex spatial stochastic phenomena. including a rock-paper-scissors game, cancer growth in response to immunotherapy, and lipid oxidation dynamics. Our approach aids in standardizing mathematical models and in generating hypotheses based on concrete mechanistic behavior across a wide range of observed spatial phenomena.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador Idioma: En Revista: PLoS One Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador Idioma: En Revista: PLoS One Ano de publicação: 2021 Tipo de documento: Article