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Systems Biologynpj Systems Biology and Applications
Peer-reviewed journal article

PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

Miguel Ponce-de-LeóniD, Arnau MontagudiD, Vincent NoëliD, Annika Meert, Gerard PradasiD, Emmanuel BarillotiD, Laurence CalzoneiD, Alfonso ValenciaiD

Abstract

Cancer progression is a complex phenomenon that spans multiple scales from molecular to cellular and intercellular. Simulations can be used to perturb the underlying mechanisms of those systems and to generate hypotheses on novel therapies. We present a new version of PhysiBoSS, a multiscale modelling framework designed to cover multiple temporal and spatial scales, that improves its integration with PhysiCell, decoupling the cell agent simulations with the internal Boolean model in an easy-to-maintain computational framework. PhysiBoSS 2.0 is a redesign and reimplementation of PhysiBoSS, conceived as an add-on that expands the PhysiCell agent-based functionalities with intracellular cell signalling using MaBoSS having a decoupled, maintainable and model-agnostic design. PhysiBoSS 2.0 successfully reproduces simulations reported in the former version and expands its functionalities such as using user-defined models and cells specifications, having mechanistic submodels of substrate internalisation with ODEs and enabling the study of drug synergies. PhysiBoSS 2.0 is open-source and publicly available on GitHub (https://github.com/PhysiBoSS/PhysiBoSS) under the BSD 3-clause license with several repositories of accompanying interoperable tools. Additionally, a nanoHUB tool has been set up to ease the use of PhysiBoSS 2.0 (https://nanohub.org/tools/pba4tnf/).

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02 /Specification & Classification

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