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Population Interaction Model:

VT iGEM Project 2007: Engineering an Epidemic

[Back to Modeling Updates] [Infection Model] [Population Interaction Model]

Hybrid Simulator
July 11, 2007

The simulator consists of an executable C++ program called hybridsim that's capable of utilizing either the gillespie algorithm, ordinary differential equations, or a combination of both. In order to effectively use this program, we have written a user friendly matlab program that organizes the data and displays it to the user. It has various functions that allow it to run multiple simulations consecutively and display the results in a time plot with error bars, histogram images, 3d histograms, color coded images showing multiple wells, and movies showing migration among many different wells. In order to simulate the migration of cells in our lab, we are using 96 well plates and a liquid handling system to mix the contents of the wells. The liquid handling system derives its instructions for mixing from an excel file that tells the machine how much to take from one well and where to dispense it. The matlab program can read in this file and simulate the mixing algorithm of the liquid handling system. The program is continually being updated for efficiency and function.

Creating Movies
July 12, 2007

We have used the hybrid simulator and the Matlab script to make "movies" of the infection spreading from well to well. Click here to see the movie on our internally hosted wiki. This video requires that you have the divx codec installed. If the movie doesn't play, go to [http://www.divx.com here] and install the latest version.

Histograms and Timeplots
July 12, 2007

If the user specifies that only one well is simulated, the program provides a new set of visualization tools to examine the specific data. Multiple simulations are run to show a variance for the possible paths that the real biological model might take. The program generates 3d histograms and image maps to organize the data and show consistency. Error bar time plots are created to give the user a more quantitative description of the data. Here is a sample of the visuals that are outputted:


Migration Events
July 12, 2007

When the wells are mixed at each iteration of simple diffusion. The program takes snap shots right before the migration occurs. This gives a quick overall picture of what happened during the simulation.

For Example with Uninfected Bacteria:



Time Plots for Multiple Diffusions
July 12, 2007

The program provides time plots of what happened during all iterations of diffusion. After the simulation has finished, the user can access the data and observe what happened to each species in any of the 96 wells. Below is a sample of a time plot for lytic and uninfected bacteria:


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