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STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python
We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process...
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Formato: | Texto |
Lenguaje: | English |
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Frontiers Research Foundation
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2706651/ https://www.ncbi.nlm.nih.gov/pubmed/19623245 http://dx.doi.org/10.3389/neuro.11.015.2009 |
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author | Wils, Stefan Schutter, Erik De |
author_facet | Wils, Stefan Schutter, Erik De |
author_sort | Wils, Stefan |
collection | PubMed |
description | We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. |
format | Text |
id | pubmed-2706651 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-27066512009-07-21 STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python Wils, Stefan Schutter, Erik De Front Neuroinformatics Neuroscience We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. Frontiers Research Foundation 2009-06-29 /pmc/articles/PMC2706651/ /pubmed/19623245 http://dx.doi.org/10.3389/neuro.11.015.2009 Text en Copyright © 2009 Wils and De Schutter. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited. |
spellingShingle | Neuroscience Wils, Stefan Schutter, Erik De STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title | STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title_full | STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title_fullStr | STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title_full_unstemmed | STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title_short | STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python |
title_sort | steps: modeling and simulating complex reaction-diffusion systems with python |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2706651/ https://www.ncbi.nlm.nih.gov/pubmed/19623245 http://dx.doi.org/10.3389/neuro.11.015.2009 |
work_keys_str_mv | AT wilsstefan stepsmodelingandsimulatingcomplexreactiondiffusionsystemswithpython AT schuttererikde stepsmodelingandsimulatingcomplexreactiondiffusionsystemswithpython |