Mocafe: a comprehensive Python library for simulating cancer development with Phase Field Models

Author:

Pradelli Franco1ORCID,Minervini Giovanni1,Tosatto Silvio C E1ORCID

Affiliation:

1. Department of Biomedical Sciences, University of Padova , 35121 Padova, Italy

Abstract

Abstract Summary Mathematical models are effective in studying cancer development at different scales from metabolism to tissue. Phase Field Models (PFMs) have been shown to reproduce accurately cancer growth and other related phenomena, including expression of relevant molecules, extracellular matrix remodeling and angiogenesis. However, implementations of such models are rarely published, reducing access to these techniques. To reduce this gap, we developed Mocafe, a modular open-source Python package that implements some of the most important PFMs reported in the literature. Mocafe is designed to handle both PFMs purely based on differential equations and hybrid agent-based PFMs. Moreover, Mocafe is meant to be extensible, allowing the inclusion of new models in future releases. Availability and implementation Mocafe is a Python package based on FEniCS, a popular computing platform for solving partial differential equations. The source code, extensive documentation and demos are provided on GitHub at URL: https://github.com/BioComputingUP/mocafe. Moreover, we uploaded on Zenodo an archive of the package, which is available at https://doi.org/10.5281/zenodo.6366052.

Funder

Fondazione AIRC per la Ricerca sul Cancro

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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