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BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology

Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing inter...

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Autores principales: Gorochowski, Thomas E., Matyjaszkiewicz, Antoni, Todd, Thomas, Oak, Neeraj, Kowalska, Kira, Reid, Stephen, Tsaneva-Atanasova, Krasimira T., Savery, Nigel J., Grierson, Claire S., di Bernardo, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427305/
https://www.ncbi.nlm.nih.gov/pubmed/22936991
http://dx.doi.org/10.1371/journal.pone.0042790
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author Gorochowski, Thomas E.
Matyjaszkiewicz, Antoni
Todd, Thomas
Oak, Neeraj
Kowalska, Kira
Reid, Stephen
Tsaneva-Atanasova, Krasimira T.
Savery, Nigel J.
Grierson, Claire S.
di Bernardo, Mario
author_facet Gorochowski, Thomas E.
Matyjaszkiewicz, Antoni
Todd, Thomas
Oak, Neeraj
Kowalska, Kira
Reid, Stephen
Tsaneva-Atanasova, Krasimira T.
Savery, Nigel J.
Grierson, Claire S.
di Bernardo, Mario
author_sort Gorochowski, Thomas E.
collection PubMed
description Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.
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spelling pubmed-34273052012-08-30 BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology Gorochowski, Thomas E. Matyjaszkiewicz, Antoni Todd, Thomas Oak, Neeraj Kowalska, Kira Reid, Stephen Tsaneva-Atanasova, Krasimira T. Savery, Nigel J. Grierson, Claire S. di Bernardo, Mario PLoS One Research Article Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher. Public Library of Science 2012-08-24 /pmc/articles/PMC3427305/ /pubmed/22936991 http://dx.doi.org/10.1371/journal.pone.0042790 Text en © 2012 Gorochowski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Gorochowski, Thomas E.
Matyjaszkiewicz, Antoni
Todd, Thomas
Oak, Neeraj
Kowalska, Kira
Reid, Stephen
Tsaneva-Atanasova, Krasimira T.
Savery, Nigel J.
Grierson, Claire S.
di Bernardo, Mario
BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title_full BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title_fullStr BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title_full_unstemmed BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title_short BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology
title_sort bsim: an agent-based tool for modeling bacterial populations in systems and synthetic biology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427305/
https://www.ncbi.nlm.nih.gov/pubmed/22936991
http://dx.doi.org/10.1371/journal.pone.0042790
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