Virginia Tech

From 2007.igem.org

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Our project is particularly important because it is important to be able to predict early whether or not an infection will develop into an epidemic. It is important to know how to localize an infection to prevent the development of an epidemic. By modeling and experimentally testing the effects of air traffic on an epidemic, we can determine at what point an infection becomes an epidemic.  
Our project is particularly important because it is important to be able to predict early whether or not an infection will develop into an epidemic. It is important to know how to localize an infection to prevent the development of an epidemic. By modeling and experimentally testing the effects of air traffic on an epidemic, we can determine at what point an infection becomes an epidemic.  
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After matching our models to our experimental data, we hope to be able to publish some of our findings.
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Revision as of 03:38, 24 October 2007

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The Virginia Tech iGEM project for 2007 is to engineer an epidemic. This will allow us to model and observe epidemic development within and between populations. By modeling and observing epidemic development, we hope to be able to understand events from the beginning of an epidemic. We will be able to do this by designing a network for the spread of infection. Our model will be multi-scaled and will include modeling a bacterial growth curve, modeling an infection of a single population, and modeling a muliple population infection. After developing the models, we will be able to verify it experimentally.

Our project is particularly important because it is important to be able to predict early whether or not an infection will develop into an epidemic. It is important to know how to localize an infection to prevent the development of an epidemic. By modeling and experimentally testing the effects of air traffic on an epidemic, we can determine at what point an infection becomes an epidemic.

After matching our models to our experimental data, we hope to be able to publish some of our findings.

We would like to thank our sponsors: