  In our article we present a computational model for the simulation of
self-propelled anisotropic bacteria. To this end we use a self-propelled
particle model and augment it with a statistical algorithm for the
run-and-tumble motion. We derive an equation for the distribution of
reorientations of the bacteria that we use to analyze the statistics of the
random walk and that allows us to tune the behavior of our model to the
characteristics of an E.coli bacterium. We validate our implementation in terms
of a single swimmer and demonstrate that our model is capable of reproducing
E.coli's run-and-tumble motion with excellent accuracy.
