A modeling and simulation language for biological cells with coupled mechanical and chemical processes

TL;DR

This paper introduces a specialized modeling language and simulation engine designed for biological cells, enabling natural representation and efficient simulation of complex coupled mechanical and chemical cellular processes.

Contribution

The authors develop a spatial hybrid systems modeling language, compiler, and mesh-free simulation engine tailored for biological cell dynamics with coupled processes.

Findings

Enables natural, domain-specific model descriptions

Supports simulation of dynamic, inhomogeneous cellular phenomena

Efficiently computes time evolution of complex cellular interactions

Abstract

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, or migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language to describe cellular dynamics must be able to naturally represent complex intra and extra-cellular spatial structures, and coupled mechanical, chemical and electrical processes. In order to be useful to domain experts, a modeling language should be based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.