A Hybrid Agent-Based Model of Chemotaxis

Abstract

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 10 3 cells and 1.2x10 6 molecules. The simulation is efficient and the results are agreeable with laboratory experiments.

Behavioural Representation of the Aorta by Utilizing Windkessel and Agent-Based Modelling

“…Al-Adwan et al (2013) design an intelligentbased cascaded control structure over titration process, and present the performance of the proposed fuzzy controller as adaptive using the genetic algorithm-based tuner. Guo and Tay (2007) propose a hybrid agent-based modelling approach where biological cells are modelled as individuals (agents) whereas chemical molecules are modelled as quantities. They demonstrate the efficacy of this approach with a chemotaxis model.…”