Team:UCL/Modeling

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<p class="major_title">RELATED NEUROSCIENCE</p>
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<p class="major_title">DRY LAB</p>
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<p class="minor_title">Modelling The Treatment And Finding New Parts</p>
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Mathematical modelling provides a powerful tool for scientists of all disciplines, allowing inspection and manipulation of a system in ways which are unachievable in the lab. In the context of biology, we can use mathematical models to study the behaviour of a single cell or an entire ecosystem. In fact, inspecting a mathematical model is very much like a laboratory experiment – the main difference being that in modelling, the environment is artificial. <br><br>
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Our project this year blends the fields of synthetic biology and neuroscience. We aim to demonstrate that genetic engineering techniques can be applied to the central nervous system, in order to rectify abnormalities in, for example, the brain on a cellular and/or macromolecular level. Such a novel application of synthetic biology could offer new ways to treat certain brain diseases, such as Alzheimer’s disease, for which modern pharmaceutical treatment is purely symptomatic.<br><br>
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Alzheimer’s disease is the most prevalent form of dementia. Symptoms include memory loss, mood fluctuations and problems with communication and reasoning. It is a physical, degenerative condition that causes cell death in the brain.
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Mathematical modelling provides a powerful tool for scientists of all disciplines, allowing inspection and manipulation of a system in ways which are unachievable in the lab. In the context of biology, we can use mathematical models to study the behaviour of a single cell or an entire ecosystem. In fact, inspecting a mathematical model is very much like a laboratory experiment – the main difference being that in modelling, the environment is artificial.
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For all the complex calculations and mechanisms behind a model, it is without much worth if it cannot produce useful results. In general, 'useful results' are defined as successful predictions about the effects of modifying some parameter - if we can use a model to determine the effect of each variable upon the outcome, we can better design our system in the real world.
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<p class="abstract_text">There are many hypotheses on the causes for Alzheimer’s disease, though there are three accepted signs in the brain: plaques, tangles and cell death. We focus on the so called ‘Amyloid Hypothesis’.  
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Since Westminster's iGEM team had not produced a model of their own, and their project has several similarities to ours, we have constructed an additional model, also in C#, and sent this to Westminster's team for them to use. The model simulates bed bugs moving randomly in a cubic room. One of their proposed "blood traps" is integrated into the simulation, which visually demonstrates bed bugs being attracted and then subsequently killed by the device.
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<p class="abstract_text">Microglia are the resident, mobile immune cells in the brain, performing many of the same roles as one’s white blood cells. In our project, we try to use microglia as a chassis for our genetic circuit.  
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<p class="abstract_text">Using bioinformatics we can identify key genes whose dysfunction drives disease states. In so doing, we are should be able to come up with new parts that target these dysfunctional genes to increase the efficacy of synthetic biological constructs.
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Latest revision as of 03:56, 5 October 2013

DRY LAB

Modelling The Treatment And Finding New Parts

Mathematical modelling provides a powerful tool for scientists of all disciplines, allowing inspection and manipulation of a system in ways which are unachievable in the lab. In the context of biology, we can use mathematical models to study the behaviour of a single cell or an entire ecosystem. In fact, inspecting a mathematical model is very much like a laboratory experiment – the main difference being that in modelling, the environment is artificial.

Click the abstracts below to read more.

Model Overview

Mathematical modelling provides a powerful tool for scientists of all disciplines, allowing inspection and manipulation of a system in ways which are unachievable in the lab. In the context of biology, we can use mathematical models to study the behaviour of a single cell or an entire ecosystem. In fact, inspecting a mathematical model is very much like a laboratory experiment – the main difference being that in modelling, the environment is artificial.

Simulation Results

For all the complex calculations and mechanisms behind a model, it is without much worth if it cannot produce useful results. In general, 'useful results' are defined as successful predictions about the effects of modifying some parameter - if we can use a model to determine the effect of each variable upon the outcome, we can better design our system in the real world.

Westminster collaboration

Since Westminster's iGEM team had not produced a model of their own, and their project has several similarities to ours, we have constructed an additional model, also in C#, and sent this to Westminster's team for them to use. The model simulates bed bugs moving randomly in a cubic room. One of their proposed "blood traps" is integrated into the simulation, which visually demonstrates bed bugs being attracted and then subsequently killed by the device.

Bioinformatics

Using bioinformatics we can identify key genes whose dysfunction drives disease states. In so doing, we are should be able to come up with new parts that target these dysfunctional genes to increase the efficacy of synthetic biological constructs.

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