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Please note

The simulation needs a Java-Plugin (1.3.x) installed for your internet browser. If you do not already have one installed, the browser will prompt you to download the Plugin from “Sun”, who is the inventor of Java. Please download the JRE (=Java runtime environment) into a directory on your computer (e.g. “c:\temp”), execute the downloaded file for installation on your system (double-click on the file). Afterwards you will be able to reload the simulation page. Maybe you will have to restart your browser to succeed.

Run the simulation

Please click here.

Description of the simulation

In contrast to the model focusing on the propagation of the cAMP waves, this model focuses on the movement of the amoebas. As in the stationary model, the cells react to a cAMP concentration above a certain threshold by additionally releasing cAMP into their environment. But there is another (lower) threshold, that is related to the cells movement behavior. If there is a cAMP concentration above this threshold, cells move towards the direction o the highest cAMP level (chemotaxis). If the cAMP level is below this threshold, the cells move randomly or stay where they are (depending on your simulation settings). Initially, the simulation starts with a strong cAMP signal in the center of the simulated area to initiate the aggregation behavior.


  • The slider density sets the density of cells
  • The slider period sets the length of the refractory period.
  • The slider release-threshold sets the cAMP threshold for releasing additional cAMP into the environment
  • The slider following-threshold sets the cAMP threshold for actively following the cAMP gradient (uphill!)
  • Using the slider view-mode, you can switch between several modes of view.
  • The switch base-random-walk determines whether the cells move randomly or stay motionless when they face a cAMP concentration below the following-threshold


  • Test for effects in changing the refractory period and in changing the threshold
  • Test for the minimum needed density to end up with one single “colony” at the end.
  • Plo density versus numer of separated “colonies” at the end.
  • Compare that to the same results in the example on percolation theory  delivered with NetLogo called “forst fire”


This are typical forms of slime molds:


This is how this is predicted by the simulation:

This picture shows the predicted propagation of the cAMP signal:


The model was inspired from Scott Camazines StarLogo-Model, that can be downloaded from his site.

The simulation was written in NetLogo by: Thomas Schmickl, Department for Zoology, Karl-Franzens-University Graz, Austria (Europe), (preferred adress),

Further readings

  • Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraulaz G. and Bonabeau E. (2001) Self-Organization in biological systems. Princeton University Press.

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