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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
John Marshall, Koji Morikawa, Nicholas Manoukis, Charles Taylor
Department of Ecology and Evolutionary Biology, University of California, Los Angeles

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0:09 Introduction9

0:21 Subscription Lock21

3:43 Using Mathematical Modelling to Understand Basic Mosquito Biology223

8:17 Modelling the Movement of Different Subspecies of A. gambiae497

13:37 Molelling Movement of Transposable Elements Through A. gambiae Subs817

17:42 Ethical Considerations for Releasing Genetically-Modified Mosquitoe1062

20:27 End Credits1227
Abstract
Charles Taylor and John Marshall explain the utility of mathematical modeling for evaluating the effectiveness of population replacement strategy. Insight is given into how computational models can provide information on the population dynamics of mosquitoes and the spread of transposable elements through A. gambiae subspecies. The ethical considerations of releasing genetically modified mosquitoes into the wild are discussed.
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Cite this Article
Marshall J, Morikawa K, Manoukis N, Taylor C (2007). Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling. JoVE. 5. http://www.jove.com/index/details.stp?id=227, doi: 10.3791/227
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12/07/2008 8:50:55 AM
aurore responded with a statement of type: Neutral

Hi,

I am a french student in Biotechnology at the University of Strasbourg.

In order to obtain my 5 years diploma we have a project to carry out. We have to create a fictive start up in Biotechnology.

Our aim is to produce mosquitoes resistant to malaria. In order to do this we  would like to perform mathematical modeling. I

would like to know if the program used in your experiment could be used in our "fictive start up". Is it a free or could you provide

it to us  in our fictive start up ?

 

Thanks for your time and consideration

 

Aurore-Cécile Valfort

 

 

 

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07/04/2007

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doi: 10.3791/227 

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Journal of Visualized Experiments (JoVE) is an online research journal employing visualization to increase reproducibility and transparency in biological sciences.

 

ISSN 1940-087X

 

 

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