Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84456
Title: A hybrid agent-based approach for modeling microbiological systems
Authors: Guo, Zaiyi.
Sloot, Peter M. A.
Tay, Joc Cing.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2008
Source: Guo, Z., Sloot, P. M. A., & Tay, J. C. (2008). A hybrid agent-based approach for modeling microbiological systems. Journal of Theoretical Biology, 255(2), 163-175.
Series/Report no.: Journal of theoretical biology
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 103 cells and 1.2×106 molecules. The model produces cell migration patterns that are comparable to laboratory observations.
URI: https://hdl.handle.net/10356/84456
http://hdl.handle.net/10220/10170
DOI: http://dx.doi.org/10.1016/j.jtbi.2008.08.008
Rights: © 2008 Elsevier Ltd.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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