Team:Aberdeen Scotland/Modeling

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<li class="curr"><a class="curr" href="#">Overview</a></li>
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<li class="curr"><a class="curr" href="http://2014.igem.org/Team:Aberdeen_Scotland/Modeling">Introduction</a></li>
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<li><a href="#">Quorum Sensing</a></li>
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<li><a href="http://2014.igem.org/Team:Aberdeen_Scotland/Modeling/QS">Quorum Sensing</a></li>
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<h1>Aberdeen iGEM Team 2014</h1>
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<h1>Modelling Aims</h1>
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<h3>Wake up to the Sleeping Sickness</h3>
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<p>Hi, there. We are a team of Aberdeen Uni undergrads trying to do our part in the fight against Sleeping Sickness. There's six of us - 5 biologists and 1 physicist. We are very excited to be able to take part in iGEM and we would like to take you on a tour around our project.</p>
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<h3>Purpose</h3>
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<p>We have worked all summer towards what we hope would turn out to be some peace of mind for a lot of people. The goal is to develop a novel method for diagnosing Trypanosomiasis. A simpler, cheaper alternative to current methods that would be more versatile in developing countries and their remote regions. We wish to create a test that would be portable, endure harsh environmental conditions and most importantly be sensitive to the early stages of the disease.</p>
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<p>This would give a lot of unsuspecting sufferers the chance to get diagnosed early. This way they can get cured quickly, before the disease reaches its later stages, when it is virtually incurable.</p>
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<p>In order to verify and characterize our diagnostic system we created mathematical models for each individual component. Modeling and simulations were essential
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techniques that guided our approach from design to completion. As the main point of interest in our system was inter-cellular communication and its optimization, we
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employed ODEs and PDEs as our main mathematical tools.</p>
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<img src="http://2014.igem.org/wiki/images/a/a7/AjkIkdjfmkJ.png">
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<p>You can find our official iGEM Registry Page <a href="http://igem.org/Team.cgi?year=2014&team_name=Aberdeen_Scotland">here</a>.</p>
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<h3>Quorum Sensing</h3>
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<p>We developed a spacial model for analyzing Quorum Sensing between cells and then studied it under our system desired conditions. This gave us insight into how
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best structure our assay.</p>
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<h3>GFP Response</h3>
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<p>By simulating GFP response we made sure our system will react in a predictable manner and in an appropriate amount of time. We ensured that simulations agreed with
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data so that we can rely on reproducibility.</p>
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<h3>Assay Sensitivity</h3>
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<p>As with any other test, sensitivity is a main factor. The test needed to be sensitive enough to detect HAT, but also tolerant to noise, so that false-positives
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were minimized. We explored the process of antibody binding to make sure we meet those criteria.</p>
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Latest revision as of 02:20, 18 October 2014

Team:Aberdeen Scotland/Modelling - 2014.ogem.org



Modelling Aims


Purpose

In order to verify and characterize our diagnostic system we created mathematical models for each individual component. Modeling and simulations were essential techniques that guided our approach from design to completion. As the main point of interest in our system was inter-cellular communication and its optimization, we employed ODEs and PDEs as our main mathematical tools.

Quorum Sensing

We developed a spacial model for analyzing Quorum Sensing between cells and then studied it under our system desired conditions. This gave us insight into how best structure our assay.

GFP Response

By simulating GFP response we made sure our system will react in a predictable manner and in an appropriate amount of time. We ensured that simulations agreed with data so that we can rely on reproducibility.

Assay Sensitivity

As with any other test, sensitivity is a main factor. The test needed to be sensitive enough to detect HAT, but also tolerant to noise, so that false-positives were minimized. We explored the process of antibody binding to make sure we meet those criteria.