A Monte Carlo Simulation on Clustering Dynamics of Social Amoebae

TL;DR

This paper introduces a Monte Carlo simulation model for social amoebae clustering, capturing key biological behaviors and reproducing experimental phenomena, providing insights into aggregation dynamics.

Contribution

The paper presents a novel discrete Monte Carlo simulation model that incorporates biological signaling and movement behaviors of social amoebae.

Findings

Simulation reveals potential equilibrium states of aggregation time.

Model reproduces observed experimental phenomena.

Provides insights into the dynamics of amoebae clustering.

Abstract

A discrete model for computer simulations of the clustering dynamics of Social Amoebae is presented. This model incorporates the wavelike propagation of extracellular signaling cAMP, the sporadic firing of cells at early stage of aggregation, the signal relaying as a response to stimulus, the inertia and purposeful random walk of the cell movement. A Monte Carlo simulation is run which shows the existence of potential equilibriums of mean and variance of aggregation time. The simulation result of this model could well reproduce many phenomena observed by actual experiments.