Difference between revisions of "Team:Lambert GA"

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GOLD
 
GOLD
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<div id="subheading1">Awards</div>
 
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Best Presentation
 
Best Presentation
Best Hardware  
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Best Hardware
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Best Measurement
 
Best Measurement
Best Integrated Human Practices
 
 
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Best Integrated Human Practices
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<div id="subheading1">Nominations</div>
 
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Nominated Best Wiki
 
Nominated Best Wiki
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Nominated Best Poster
 
Nominated Best Poster
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Nominated Best Model
 
Nominated Best Model
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Nominated Best Project Design
 
Nominated Best Project Design
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Revision as of 21:39, 2 November 2018

C A P T I V A T E
CAPTURE THE DATA | ACTIVATE THE RESPONSE
2018 Lambert iGEM
Our Project



Vibrio cholerae, a pathogenic waterborne bacteria, impacts millions of people annually. Cases are most prevalent in developing countries with a lack of practical diagnostic methods and clean water. Lambert iGEM created a proactive, inexpensive diagnostic kit for V. cholerae detection utilizing frugal hardware devices and toehold switches. Utilizing rainfall, conflict, and cholera case/death data, CALM is able to accurately model the Yemeni V. cholerae outbreak, forecasting outbreaks weeks in advance. These riboregulators activate gene expression in response to predetermined RNA sequences. Engineering E. coli to detect V. cholerae, we targeted ctxB, a non-toxic subunit of a gene specific to all pathogenic V. cholerae. Our Chrome-Q system quantifies aquatic V. cholerae presence utilizing HSV values while the Color-Q app inputs data into our machine learning model, CALM. With this diagnostic kit, Lambert iGEM addresses V. cholerae epidemics using Yemen as a test case by predicting outbreaks, thus providing low-cost sustainable diagnostic tools while enhancing quality prediction.












Medal
GOLD

Awards

Best Presentation
Best Hardware
Best Measurement
Best Integrated Human Practices

Nominations

Nominated Best Wiki
Nominated Best Poster
Nominated Best Model
Nominated Best Project Design