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PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling

MOTIVATION: Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intr...

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Autores principales: Letort, Gaelle, Montagud, Arnau, Stoll, Gautier, Heiland, Randy, Barillot, Emmanuel, Macklin, Paul, Zinovyev, Andrei, Calzone, Laurence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449758/
https://www.ncbi.nlm.nih.gov/pubmed/30169736
http://dx.doi.org/10.1093/bioinformatics/bty766
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author Letort, Gaelle
Montagud, Arnau
Stoll, Gautier
Heiland, Randy
Barillot, Emmanuel
Macklin, Paul
Zinovyev, Andrei
Calzone, Laurence
author_facet Letort, Gaelle
Montagud, Arnau
Stoll, Gautier
Heiland, Randy
Barillot, Emmanuel
Macklin, Paul
Zinovyev, Andrei
Calzone, Laurence
author_sort Letort, Gaelle
collection PubMed
description MOTIVATION: Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). RESULTS: PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. AVAILABILITY AND IMPLEMENTATION: PhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-64497582019-04-09 PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling Letort, Gaelle Montagud, Arnau Stoll, Gautier Heiland, Randy Barillot, Emmanuel Macklin, Paul Zinovyev, Andrei Calzone, Laurence Bioinformatics Original Papers MOTIVATION: Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). RESULTS: PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. AVAILABILITY AND IMPLEMENTATION: PhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-04-01 2018-08-30 /pmc/articles/PMC6449758/ /pubmed/30169736 http://dx.doi.org/10.1093/bioinformatics/bty766 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Letort, Gaelle
Montagud, Arnau
Stoll, Gautier
Heiland, Randy
Barillot, Emmanuel
Macklin, Paul
Zinovyev, Andrei
Calzone, Laurence
PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title_full PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title_fullStr PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title_full_unstemmed PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title_short PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
title_sort physiboss: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449758/
https://www.ncbi.nlm.nih.gov/pubmed/30169736
http://dx.doi.org/10.1093/bioinformatics/bty766
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