Cargando…

eSTGt: a programming and simulation environment for population dynamics

BACKGROUND: We have previously presented a formal language for describing population dynamics based on environment-dependent Stochastic Tree Grammars (eSTG). The language captures in broad terms the effect of the changing environment while abstracting away details on interaction among individuals. A...

Descripción completa

Detalles Bibliográficos
Autores principales: Spiro, Adam, Shapiro, Ehud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847376/
https://www.ncbi.nlm.nih.gov/pubmed/27117841
http://dx.doi.org/10.1186/s12859-016-1004-y
_version_ 1782429205389115392
author Spiro, Adam
Shapiro, Ehud
author_facet Spiro, Adam
Shapiro, Ehud
author_sort Spiro, Adam
collection PubMed
description BACKGROUND: We have previously presented a formal language for describing population dynamics based on environment-dependent Stochastic Tree Grammars (eSTG). The language captures in broad terms the effect of the changing environment while abstracting away details on interaction among individuals. An eSTG program consists of a set of stochastic tree grammar transition rules that are context-free. Transition rule probabilities and rates, however, can depend on global parameters such as population size, generation count and elapsed time. In addition, each individual may have an internal state, which can change during transitions. RESULTS: This paper presents eSTGt (eSTG tool), an eSTG programming and simulation environment. When executing a program, the tool generates the corresponding lineage trees as well as the internal states values, which can then be analyzed either through the tool’s GUI or using MATLAB’s command-line environment. CONCLUSIONS: The presented tool allows researchers to use existing biological knowledge in order to model the dynamics of a developmental process and analyze its behavior throughout the historical events. Simulated lineage trees can be used to validate various hypotheses in silico and to predict the behavior of dynamical systems under various conditions. Written under MATLAB environment, the tool also enables to easily integrate the output data within the user’s downstream analysis.
format Online
Article
Text
id pubmed-4847376
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-48473762016-05-04 eSTGt: a programming and simulation environment for population dynamics Spiro, Adam Shapiro, Ehud BMC Bioinformatics Software BACKGROUND: We have previously presented a formal language for describing population dynamics based on environment-dependent Stochastic Tree Grammars (eSTG). The language captures in broad terms the effect of the changing environment while abstracting away details on interaction among individuals. An eSTG program consists of a set of stochastic tree grammar transition rules that are context-free. Transition rule probabilities and rates, however, can depend on global parameters such as population size, generation count and elapsed time. In addition, each individual may have an internal state, which can change during transitions. RESULTS: This paper presents eSTGt (eSTG tool), an eSTG programming and simulation environment. When executing a program, the tool generates the corresponding lineage trees as well as the internal states values, which can then be analyzed either through the tool’s GUI or using MATLAB’s command-line environment. CONCLUSIONS: The presented tool allows researchers to use existing biological knowledge in order to model the dynamics of a developmental process and analyze its behavior throughout the historical events. Simulated lineage trees can be used to validate various hypotheses in silico and to predict the behavior of dynamical systems under various conditions. Written under MATLAB environment, the tool also enables to easily integrate the output data within the user’s downstream analysis. BioMed Central 2016-04-27 /pmc/articles/PMC4847376/ /pubmed/27117841 http://dx.doi.org/10.1186/s12859-016-1004-y Text en © Spiro and Shapiro. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Spiro, Adam
Shapiro, Ehud
eSTGt: a programming and simulation environment for population dynamics
title eSTGt: a programming and simulation environment for population dynamics
title_full eSTGt: a programming and simulation environment for population dynamics
title_fullStr eSTGt: a programming and simulation environment for population dynamics
title_full_unstemmed eSTGt: a programming and simulation environment for population dynamics
title_short eSTGt: a programming and simulation environment for population dynamics
title_sort estgt: a programming and simulation environment for population dynamics
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847376/
https://www.ncbi.nlm.nih.gov/pubmed/27117841
http://dx.doi.org/10.1186/s12859-016-1004-y
work_keys_str_mv AT spiroadam estgtaprogrammingandsimulationenvironmentforpopulationdynamics
AT shapiroehud estgtaprogrammingandsimulationenvironmentforpopulationdynamics