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 103 cells and 1.2x106 molecules. The simulation is efficient and the results are agreeable with laboratory experiments.
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Guo, Z., Tay, J.C. (2007). A Hybrid Agent-Based Model of Chemotaxis. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4487. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72584-8_16
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DOI: https://doi.org/10.1007/978-3-540-72584-8_16
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