Building multiscale models with PhysiBoSS, an agent-based modeling tool

Multiscale models provide a unique tool for analyzing complex processes that study events occurring at different scales across space and time. In the context of biological systems, such models can simulate mechanisms happening at the intracellular level such as signaling, and at the extracellular level where cells communicate and coordinate with other cells. These models aim to understand the impact of genetic or environmental deregulation observed in complex diseases, describe the interplay between a pathological tissue and the immune system, and suggest strategies to revert the diseased phenotypes. The construction of these multiscale models remains a very complex task, including the choice of the components to consider, the level of details of the processes to simulate, or the fitting of the parameters to the data. One additional difficulty is the expert knowledge needed to program these models in languages such as C++ or Python, which may discourage the participation of non-experts. Simplifying this process through structured description formalisms-coupled with a graphical interface-is crucial in making modeling more accessible to the broader scientific community, as well as streamlining the process for advanced users. This article introduces three examples of multiscale models which rely on the framework PhysiBoSS, an add-on of PhysiCell that includes intracellular descriptions as continuous time Boolean models to the agent-based approach. The article demonstrates how to construct these models more easily, relying on PhysiCell Studio, the PhysiCell Graphical User Interface. A step-by-step tutorial is provided as Supplementary Material and all models are provided at https://physiboss.github.io/tutorial/.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2024-09-23
DOI
https://doi.org/10.1093/bib/bbae509
Citations
6
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
2.37

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article

Building multiscale models with PhysiBoSS, an agent-based modeling tool

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6 citations
Briefings in Bioinformatics
Mathematical Biology Tumor Growth
2.37
article

Building multiscale models with PhysiBoSS, an agent-based modeling tool

Paul Macklin, Randy Heiland, Laurence Calzone, Emmanuel Barillot, Marco Ruscone, Andrea Checcoli, Vincent Noël
article en
6 citations

Abstract

Multiscale models provide a unique tool for analyzing complex processes that study events occurring at different scales across space and time. In the context of biological systems, such models can simulate mechanisms happening at the intracellular level such as signaling, and at the extracellular level where cells communicate and coordinate with other cells. These models aim to understand the impact of genetic or environmental deregulation observed in complex diseases, describe the interplay between a pathological tissue and the immune system, and suggest strategies to revert the diseased phenotypes. The construction of these multiscale models remains a very complex task, including the choice of the components to consider, the level of details of the processes to simulate, or the fitting of the parameters to the data. One additional difficulty is the expert knowledge needed to program these models in languages such as C++ or Python, which may discourage the participation of non-experts. Simplifying this process through structured description formalisms-coupled with a graphical interface-is crucial in making modeling more accessible to the broader scientific community, as well as streamlining the process for advanced users. This article introduces three examples of multiscale models which rely on the framework PhysiBoSS, an add-on of PhysiCell that includes intracellular descriptions as continuous time Boolean models to the agent-based approach. The article demonstrates how to construct these models more easily, relying on PhysiCell Studio, the PhysiCell Graphical User Interface. A step-by-step tutorial is provided as Supplementary Material and all models are provided at https://physiboss.github.io/tutorial/.

Briefings in BioinformaticsVol. 25(6)
Inserm (FR), Université Paris Sciences et Lettres (FR), Sorbonne Université (FR), Centre de Recherche des Cordeliers (FR), Indiana University Bloomington (US), École Nationale Supérieure des Mines de Paris (FR), Institut Curie (FR)
National Science Foundation, Jayne Koskinas Ted Giovanis Foundation for Health and Policy, European Commission, Agence Nationale de la Recherche, Institut National de la Santé et de la Recherche Médicale, National Institutes of Health, HORIZON EUROPE Framework Programme
Quality Education
Openalex Percentile: Top 12%
Mathematical Biology Tumor Growth
2.37
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