A hybrid agent-based approach for modeling microbiological systems

Authored by Zaiyi Guo, Peter M. A. Sloot, Joc Cing Tay

Date Published: 2008-11-21

DOI: 10.1016/j.jtbi.2008.08.008

Sponsors: No sponsors listed

Platforms: Java

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2 x 10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations. (C) 2008 Elsevier Ltd. All rights reserved.

Tags

Dynamics chemotaxis movement Multi-layered simulation models Receptor kinetics Under-agarose assay Immune-system Motility Gradients Individual-based models Dendritic cell maturation Agarose migration assay Trafficking