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

Gaelle Letort1,2,3, Arnau Montagud1,2,3, Gautier Stoll4,5,6,7

  • 1Institut Curie, PSL Research University, Paris, France.

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Summary
This summary is machine-generated.

PhysiBoSS integrates intracellular signaling with multicellular agent-based modeling for biological systems. This open-source software aids in understanding population dynamics and treatment responses.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Mathematical Modeling

Background:

  • Multicellular biological systems exhibit complexity and heterogeneity.
  • Mathematical models are crucial for understanding cell signaling, population behavior, and the extracellular environment.

Purpose of the Study:

  • To present PhysiBoSS, an open-source software combining Boolean modeling for intracellular signaling and agent-based modeling for multicellular behavior.
  • To provide a flexible and computationally efficient framework for exploring cellular and population-level responses to alterations.

Main Methods:

  • Integration of MaBoSS (Boolean modeling) for intracellular signaling.
  • Utilization of PhysiCell (agent-based modeling) for multicellular dynamics.
  • Development as an open-source software with a Docker image for accessibility.

Main Results:

  • PhysiBoSS enables the study of heterogeneous population responses to treatments and genetic modifications.
  • Demonstrated utility in analyzing cell fate decisions, treatment effects, and resistant mutant behavior.
  • Highlighted the impact of spatial information and resource competition (e.g., oxygen) on population dynamics.

Conclusions:

  • PhysiBoSS bridges the gap between single-cell genotype and emergent multicellular behavior.
  • The software is valuable for investigating complex biological phenomena, including invasion and morphogenesis.
  • Open accessibility via GitHub and Docker facilitates widespread adoption and research contribution.