Difference between revisions of "Team:CCA SanDiego/Description"

Line 2: Line 2:
 
<html>
 
<html>
  
−
<h2> Project Description </h2>
+
<h2 style="text-align:center">Description</h2>
  
−
<p>Tell us about your project, describe what moves you and why this is something important for your team.</p>
+
<p style="text-align:center">Biosensors are at the forefront of exciting developments in bioengineering and biomedical research due to their applicability in the diagnosis and treatment of debilitating diseases such as diabetes, cancer, and ALS.  They allow us to take advantage of pre-existing mechanisms in nature to detect chemicals in the body that can serve as diagnostic markers for disease.  Using high performance computing we modelled the behavior of a glucose sensing biosensor at a high resolution at the atomic level. The biosensor we modelled has the ability to fluoresce in the presence of glucose, and therefore serves as an effective monitor of blood sugar levels - a critical biomarker used for diabetes treatment.  This has monumental applications in the treatment of diabetes. Such a biosensor could be potentially coupled to an insulin producing circuit to automatically deliver needed medicine to diabetics without the use of invasive needles and injections.  Our modelling approach can be applied to simulate related biosensors, testing many iterations of possible biosensor designs without the need to perform an wet-lab experiment that would produce hazardous waste.  Our team has produced an in silico optimization and debugging biosensor template which allows for a majority of testing to be performed prior to entering a wet-lab facility.  By reducing the amount of time spent in the wet-lab, our modelling approach provides a safer, more eco-friendly testing environment. It’s as simple as saving on pipette tips - we don’t have to throw away hundreds of plastic pipet tips for one experiment.  Biosensors are a rapidly developing treatment and diagnosis tool in biomedical research, and our team has been able to utilize high-performance computer modelling to efficiently test these revolutionary devices.</p>
−
<br />
+
  
−
<h5>What should this page contain?</h5>
 
−
<ul>
 
−
<li> A clear and concise description of your project.</li>
 
−
<li>A detailed explanation of why your team chose to work on this particular project.</li>
 
−
<li>References and sources to document your research.</li>
 
−
<li>Use illustrations and other visual resources to explain your project.</li>
 
−
</ul>
 
−
 
−
 
−
<br />
 
−
<h4>Advice on writing your Project Description</h4>
 
−
 
−
<p>
 
−
We encourage you to put up a lot of information and content on your wiki, but we also encourage you to include summaries as much as possible. If you think of the sections in your project description as the sections in a publication, you should try to be consist, accurate and unambiguous in your achievements.
 
−
</p>
 
−
 
−
<p>
 
−
Judges like to read your wiki and know exactly what you have achieved. This is how you should think about these sections; from the point of view of the judge evaluating you at the end of the year.
 
−
</p>
 
−
 
−
 
−
<br />
 
−
<h4>References</h4>
 
−
<p>iGEM teams are encouraged to record references you use during the course of your research. They should be posted somewhere on your wiki so that judges and other visitors can see how you though about your project and what works inspired you.</p>
 
−
 
−
 
−
 
−
<h4>Inspiration</h4>
 
−
<p>See how other teams have described and presented their projects: </p>
 
−
 
−
<ul>
 
−
<li><a href="https://2014.igem.org/Team:Imperial/Project"> Imperial</a></li>
 
−
<li><a href="https://2014.igem.org/Team:UC_Davis/Project_Overview"> UC Davis</a></li>
 
−
<li><a href="https://2014.igem.org/Team:SYSU-Software/Overview">SYSU Software</a></li>
 
−
</ul>
 
−
 
−
</div>
 
 
</html>
 
</html>

Revision as of 22:57, 17 September 2015

Description

Biosensors are at the forefront of exciting developments in bioengineering and biomedical research due to their applicability in the diagnosis and treatment of debilitating diseases such as diabetes, cancer, and ALS. They allow us to take advantage of pre-existing mechanisms in nature to detect chemicals in the body that can serve as diagnostic markers for disease. Using high performance computing we modelled the behavior of a glucose sensing biosensor at a high resolution at the atomic level. The biosensor we modelled has the ability to fluoresce in the presence of glucose, and therefore serves as an effective monitor of blood sugar levels - a critical biomarker used for diabetes treatment. This has monumental applications in the treatment of diabetes. Such a biosensor could be potentially coupled to an insulin producing circuit to automatically deliver needed medicine to diabetics without the use of invasive needles and injections. Our modelling approach can be applied to simulate related biosensors, testing many iterations of possible biosensor designs without the need to perform an wet-lab experiment that would produce hazardous waste. Our team has produced an in silico optimization and debugging biosensor template which allows for a majority of testing to be performed prior to entering a wet-lab facility. By reducing the amount of time spent in the wet-lab, our modelling approach provides a safer, more eco-friendly testing environment. It’s as simple as saving on pipette tips - we don’t have to throw away hundreds of plastic pipet tips for one experiment. Biosensors are a rapidly developing treatment and diagnosis tool in biomedical research, and our team has been able to utilize high-performance computer modelling to efficiently test these revolutionary devices.