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Updated: Jun 21, 2025

Multiscale Investigations of Cortical Processing by Integrating Laminar Polytrodes and Optogenetics with Micro Electrocorticography in Rodents

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

Marco Ruscone^1,2,3, Andrea Checcoli^4,5, Randy Heiland⁶

¹Institut Curie, Université PSL, F-75005, Paris, France.

|July 9, 2024

Summary

This summary is machine-generated.

Multiscale models simulate biological processes across scales. The PhysiBoSS framework simplifies their creation using PhysiCell Studio, making complex disease modeling more accessible.

Keywords:

Agent-based modeling Boolean modeling Multiscale modeling

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Published on: December 4, 2021

Area of Science:

Computational Biology
Systems Biology
Biophysics

Background:

Multiscale models are essential for understanding complex biological systems across spatial and temporal scales.
Simulating intracellular and extracellular processes aids in studying diseases and immune interactions.
Model construction is complex, requiring expert programming knowledge and significant effort.

Purpose of the Study:

To introduce the PhysiBoSS framework for constructing multiscale biological models.
To demonstrate the simplification of model creation using PhysiCell Studio, a graphical user interface.
To enhance accessibility of multiscale modeling for both novice and expert researchers.

Main Methods:

Utilized the PhysiBoSS framework, an extension of PhysiCell.
Integrated intracellular continuous time Boolean models with an agent-based approach.
Employed PhysiCell Studio for graphical model construction and simulation.

Main Results:

Successfully demonstrated the construction of three distinct multiscale models.
Showcased the ease of use of PhysiCell Studio for simplifying model development.
Provided a step-by-step tutorial and accessible model repositories for reproducibility.

Conclusions:

PhysiBoSS, integrated with PhysiCell Studio, significantly simplifies the creation of complex multiscale biological models.
This approach lowers the barrier to entry for non-expert users in computational biology.
Facilitates advanced research by streamlining the modeling process for complex diseases and biological systems.