A cell-centered, agent-based framework that enables flexible environment granularities.

Area of Science:

• Computational Biology
• Biophysics
• Systems Biology

Background:

• Mechanistic explanations of cell-level phenomena traditionally use an observer perspective.
• A cell's perspective may offer novel insights into biological processes.
• Existing agent-based models often rely on lattice-based environments, limiting certain types of analysis.

Purpose of the Study:

• To present a new agent-based, discrete event framework for modeling biological phenomena.
• To enable modeling from an individual cell's perspective within an off-lattice environment.
• To facilitate the study of complex biological phenomena with improved understanding.

Main Methods:

• Developed a 2D agent-based, discrete event framework, extended to 3D.
• Utilized a dynamic Delaunay and Voronoi off-lattice environment.
• Modeled biological cells and demonstrated basic cellular behaviors in 2D and 3D.

Main Results:

• Successfully modeled biological cells and their behaviors in two- and three-dimensional space.
• Demonstrated the framework's capability to handle complex biological phenomena.
• Highlighted potential use cases and the utility of the framework in various scenarios.

Conclusions:

• The presented framework offers a novel cell-centered perspective in an off-lattice environment.
• It expands upon existing agent-centered methods in computational biology.
• The framework is expected to meet the growing demand for advanced biomimetic modeling approaches.