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Hybrid spatial Gillespie and particle tracking simulation
Motivation: Cellular signal transduction involves spatial–temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Alg...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436811/ https://www.ncbi.nlm.nih.gov/pubmed/22962480 http://dx.doi.org/10.1093/bioinformatics/bts384 |
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author | Klann, Michael Ganguly, Arnab Koeppl, Heinz |
author_facet | Klann, Michael Ganguly, Arnab Koeppl, Heinz |
author_sort | Klann, Michael |
collection | PubMed |
description | Motivation: Cellular signal transduction involves spatial–temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Algorithm (SSA) or Brownian/Smoluchowski dynamics if space and stochasticity are important. To combine the accuracy of particle-based methods with the superior performance of the SSA, we suggest a hybrid simulation. Results: The proposed simulation allows an interactive or automated switching for regions or species of interest in the cell. Especially we see an application if for instance receptor clustering at the membrane is modeled in detail and the transport through the cytoplasm is included as well. The results show the increase in performance of the overall simulation, and the limits of the approach if crowding is included. Future work will include the development of a GUI to improve control of the simulation. Availability of Implementation: www.bison.ethz.ch/research/spatial_simulations. Contact: mklann@ee.ethz.ch or koeppl@ethz.ch Supplementary/Information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3436811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-34368112012-12-12 Hybrid spatial Gillespie and particle tracking simulation Klann, Michael Ganguly, Arnab Koeppl, Heinz Bioinformatics Original Papers Motivation: Cellular signal transduction involves spatial–temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Algorithm (SSA) or Brownian/Smoluchowski dynamics if space and stochasticity are important. To combine the accuracy of particle-based methods with the superior performance of the SSA, we suggest a hybrid simulation. Results: The proposed simulation allows an interactive or automated switching for regions or species of interest in the cell. Especially we see an application if for instance receptor clustering at the membrane is modeled in detail and the transport through the cytoplasm is included as well. The results show the increase in performance of the overall simulation, and the limits of the approach if crowding is included. Future work will include the development of a GUI to improve control of the simulation. Availability of Implementation: www.bison.ethz.ch/research/spatial_simulations. Contact: mklann@ee.ethz.ch or koeppl@ethz.ch Supplementary/Information: Supplementary data are available at Bioinformatics online. Oxford University Press 2012-09-15 2012-09-03 /pmc/articles/PMC3436811/ /pubmed/22962480 http://dx.doi.org/10.1093/bioinformatics/bts384 Text en © The Author(s) (2012). Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Klann, Michael Ganguly, Arnab Koeppl, Heinz Hybrid spatial Gillespie and particle tracking simulation |
title | Hybrid spatial Gillespie and particle tracking simulation |
title_full | Hybrid spatial Gillespie and particle tracking simulation |
title_fullStr | Hybrid spatial Gillespie and particle tracking simulation |
title_full_unstemmed | Hybrid spatial Gillespie and particle tracking simulation |
title_short | Hybrid spatial Gillespie and particle tracking simulation |
title_sort | hybrid spatial gillespie and particle tracking simulation |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436811/ https://www.ncbi.nlm.nih.gov/pubmed/22962480 http://dx.doi.org/10.1093/bioinformatics/bts384 |
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