journal article·2024-06-23Open access

Bridging Continuous and Lattice-Based Models of Two-Dimensional Diffusion: A Systematic Approach for Estimating Transition Probabilities, Grid Size and Diffusivity

Tricity M. Andrew, Mansoor A. Haider

Applied Sciences· Volume 14· Issue 13

Abstract

Lattice-based models have been broadly applied in mathematical and computational modeling of biological and biomedical systems for which spatial effects are important. These discrete models commonly include diffusion of mobile constituents as a key underlying mechanism. While the direct simulation of diffusion in continuous (off-lattice) domains is possible, it is computationally intensive, particularly when multiple coupled mechanisms are involved. This study presents a systematic approach for connecting continuous models of two-dimensional diffusion with internal obstacles to discrete, lattice-based (surrogate) models of diffusion. Results from continuous model simulations on a representative domain, and over many realizations, are used to develop accurate lattice-based surrogate models by exploiting internal symmetries. Probabilities determined for the lattice-based surrogate models are also connected to theoretical diffusivities for 2D random walks on a square lattice, necessitating the calibration of a spatial grid size. This approach can facilitate the inclusion of more accurate diffusive transport models of complex media within the general framework of lattice-based models that incorporate multiple coupled mechanisms.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Probabilistic and Robust Engineering Design · Diffusion and Search Dynamics · Mathematical Biology Tumor Growth

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA

Funding

US National Science Foundation · NSF Graduate Research Fellowship

References (14)

Show source-provided references
1. Anderson, A., and Rejniak, K. (2007). Single-Cell-Based Models in Biology and Medicine, Springer Science & Business Media.10.1007/978-3-7643-8123-3 ↗
2. Simulation of the differential adhesion driven rearrangement of biological cells10.1103/PhysRevE.47.2128 ↗
3. A multiscale model for avascular tumor growth10.1529/biophysj.105.060640 ↗
4. Modelling morphogenesis: From single cells to crawling slugs10.1006/jtbi.1996.0237 ↗
5. Control of epidermal stem cell clusters by Notch-mediated lateral induction10.1016/S0012-1606(03)00107-6 ↗
6. Stochastic simulation of benign avascular tumour growth using the Potts model10.1016/S0895-7177(99)00156-9 ↗
7. Optimization and control of agent-based models in biology: A perspective10.1007/s11538-016-0225-6 ↗
8. An agent based model of integrin clustering: Exploring the role of ligand clustering, integrin homo-oligomerization, integrin-ligand affinity, membrane crowdedness and ligand mobility10.1016/j.jcp.2012.09.010 ↗
9. Agent-based modeling of cancer stem cell driven solid tumor growth10.1007/7651_2016_346 ↗
10. Constrained diffusion or immobile fraction on cell surfaces: A new interpretation10.1016/S0006-3495(96)79846-6 ↗
11. Anomalous Diffusion Due to Obstacles: A Monte Carlo Study10.1016/S0006-3495(94)80789-1 ↗
12. Single-Particle Tracking: The Distribution of Diffusion Coefficients10.1016/S0006-3495(97)78820-9 ↗
13. New insights into diffusion in 3D crowded media by Monte Carlo simulations: Effect of size, mobility and spatial distribution of obstacles10.1039/c0cp01218a ↗
14. Holmes, M.H. (2009). Introduction to the Foundations of Applied Mathematics, Springer.10.1007/978-0-387-87765-5 ↗