A Hybrid Agent-Based Model of Chemotaxis

Authors:
Zaiyi Guo;Joc Cing Tay
Affiliations:
Evolutionary and Complex Systems Program, School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore;Evolutionary and Complex Systems Program, School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Year:
2007

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Abstract

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. These choices need not necessarily be mutually exclusive. We propose a hybrid agent-based approach where biological cells are modeled as individuals (agents) while chemical molecules are kept as quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing requirements of modeling extensibility with computational tractability. We demonstrate the efficacy of this approach with a realistic model of chemotaxis based on receptor kinetics involving an assay of 103cells and 1.2x106molecules. The simulation is efficient and the results are agreeable with laboratory experiments.