A hybrid agent-based approach for modeling microbiological systems.
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 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.
Guo
Zaiyi
Z
Evolutionary and Complex Systems Program, School of Computer Engineering, Nanyang Technological University, Blk N4 #2a-32 Nanyang Avenue, Singapore 639798, Singapore.
Sloot
Peter M A
PM
Tay
Joc Cing
JC
D000818:Animals; D002468:Cell Physiological Phenomena; D002633:Chemotaxis / Q000502:physiology; D003198:Computer Simulation; D008954:Models, Biological; D008956:Models, Chemical; D011956:Receptors, Cell Surface / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology; D049490:Systems Biology
D011956:Receptors, Cell Surface