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dc.contributor.authorGuo, Zaiyi.en
dc.contributor.authorSloot, Peter M. A.en
dc.contributor.authorTay, Joc Cing.en
dc.identifier.citationGuo, 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.en
dc.description.abstractModels 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.en
dc.relation.ispartofseriesJournal of theoretical biologyen
dc.rights© 2008 Elsevier Ltd.en
dc.subjectDRNTU::Engineering::Computer science and engineeringen
dc.titleA hybrid agent-based approach for modeling microbiological systemsen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Engineeringen
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