Difference between revisions of "Team:Queens Canada/Tets"
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<a href="https://2018.igem.org/Team:Queens_Canada/Engagement"><img src="https://static.igem.org/mediawiki/2018/b/b6/T--Queens_Canada--PyMOLNoLinker.jpg" alt='nolinker' style="height=50%"/></a> | <a href="https://2018.igem.org/Team:Queens_Canada/Engagement"><img src="https://static.igem.org/mediawiki/2018/b/b6/T--Queens_Canada--PyMOLNoLinker.jpg" alt='nolinker' style="height=50%"/></a> | ||
| − | <font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Engagement">Molecular Dynamic Simulations</a></font> | + | <br><font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Engagement">Molecular Dynamic Simulations</a></font> |
<p>One of our constructs relied on linkers of sufficient length and flexibility to convert a conformational change, into signal transduction. We have achieved this through firstly modelling with <a href="https://2018.igem.org/Team:Queens_Canada/Linker_Development" target="_blank">PyMol</a> and then performing molecular dynamic simulations of the root-mean-square deviation of <a href="https://2018.igem.org/Team:Queens_Canada/Fluid_Dynamics" target="_blank"> atomic position.</p> | <p>One of our constructs relied on linkers of sufficient length and flexibility to convert a conformational change, into signal transduction. We have achieved this through firstly modelling with <a href="https://2018.igem.org/Team:Queens_Canada/Linker_Development" target="_blank">PyMol</a> and then performing molecular dynamic simulations of the root-mean-square deviation of <a href="https://2018.igem.org/Team:Queens_Canada/Fluid_Dynamics" target="_blank"> atomic position.</p> | ||
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<a href="https://2018.igem.org/Team:Queens_Canada/Collaborations"><img src="https://static.igem.org/mediawiki/2018/f/f9/T--Queens_Canada--NanoTimelapse.jpeg" style="height=50%"/></a> | <a href="https://2018.igem.org/Team:Queens_Canada/Collaborations"><img src="https://static.igem.org/mediawiki/2018/f/f9/T--Queens_Canada--NanoTimelapse.jpeg" style="height=50%"/></a> | ||
| − | <font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Collaborations">Michaelis - Menten kinetics</a></font> | + | <br><font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Collaborations">Michaelis - Menten kinetics</a></font> |
<p>Michaelis - Menten kinetics is a model used to examine enzyme kinetic. Luciferase's activity can be modeled by Michaelis-Menten kinetics as they perform the simple conversion of a substrate into a product and a photon. Our project relied on the light producing NanoLuc Luciferase as a signal in our devices. We were able to model this relationship with MATLAB. The governing equations for this model were compiled in the MATLAB, with the goal of creating a generic calculator which teams may use in the future. Known | <p>Michaelis - Menten kinetics is a model used to examine enzyme kinetic. Luciferase's activity can be modeled by Michaelis-Menten kinetics as they perform the simple conversion of a substrate into a product and a photon. Our project relied on the light producing NanoLuc Luciferase as a signal in our devices. We were able to model this relationship with MATLAB. The governing equations for this model were compiled in the MATLAB, with the goal of creating a generic calculator which teams may use in the future. Known | ||
values for concentrations and reactions rates are used as inputs, and the file produces the various | values for concentrations and reactions rates are used as inputs, and the file produces the various | ||
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<a href="https://2018.igem.org/Team:Queens_Canada/Safety"><img src="https://static.igem.org/mediawiki/2018/0/06/T--Queens_Canada--BrownianSimulation2FD.png" alt='Diagram showing Brownian simulations in a tube' style="width:50%"/></a> | <a href="https://2018.igem.org/Team:Queens_Canada/Safety"><img src="https://static.igem.org/mediawiki/2018/0/06/T--Queens_Canada--BrownianSimulation2FD.png" alt='Diagram showing Brownian simulations in a tube' style="width:50%"/></a> | ||
| − | <br><font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Safety">Fluid Dynamics</a></font> | + | <br><br><font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Safety">Fluid Dynamics</a></font> |
<p>The ultimate application of our work from this year will be in the form of a diagnostic pacifier capable of collecting saliva, mixing with an internal biosensor and generating a signal for salivary hormone quantification. Therefore we sought to model many aspects of the pacifier including: saliva flow rate, flow turbulence, and particle mixing.</p> | <p>The ultimate application of our work from this year will be in the form of a diagnostic pacifier capable of collecting saliva, mixing with an internal biosensor and generating a signal for salivary hormone quantification. Therefore we sought to model many aspects of the pacifier including: saliva flow rate, flow turbulence, and particle mixing.</p> | ||
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Revision as of 19:27, 13 October 2018
Human Practices
At team Queens Canada, we believe that proper preparation is the best way to reach a desired outcome. Accordingly, we sought to model many aspects of our project which aided in making the right choices in the lab and receiving positive results. Through the help of student on our team specializing in biomedical computing, applied mathematics, and chemical engineering, we created a number of different models that were crucial to our project design.
Molecular Dynamic Simulations
One of our constructs relied on linkers of sufficient length and flexibility to convert a conformational change, into signal transduction. We have achieved this through firstly modelling with PyMol and then performing molecular dynamic simulations of the root-mean-square deviation of atomic position.
Michaelis - Menten kinetics
Michaelis - Menten kinetics is a model used to examine enzyme kinetic. Luciferase's activity can be modeled by Michaelis-Menten kinetics as they perform the simple conversion of a substrate into a product and a photon. Our project relied on the light producing NanoLuc Luciferase as a signal in our devices. We were able to model this relationship with MATLAB. The governing equations for this model were compiled in the MATLAB, with the goal of creating a generic calculator which teams may use in the future. Known values for concentrations and reactions rates are used as inputs, and the file produces the various rates of change with respect to the concentrations.
Fluid Dynamics
The ultimate application of our work from this year will be in the form of a diagnostic pacifier capable of collecting saliva, mixing with an internal biosensor and generating a signal for salivary hormone quantification. Therefore we sought to model many aspects of the pacifier including: saliva flow rate, flow turbulence, and particle mixing.
Expert Interviews
QGEM has performed a series of interviews with physicians, professors, researchers, and support groups, regarding their unique perspectives and utility on our product. Click to learn more from our Experts, and visit our Market Direction Analysis to see the application of the consultations.
The Interlab Measurement Study
QGEM has participated in the Fifth International InterLaboratory Measurement Study to help create standardized protocols across laboratories in the synthetic biology community. Click to see our contributions on the GFP measurements this year!
Market Direction Analysis
Our team explored multiple potential uses for our device, with pressure-testing from our Expert Interviewees. After collecting input from experts and the general public, we were able to evaluate the safety, sustainability, and practicality of each marketing approach. Click to explore the how we integrated the feedback into the development of our device’s purpose and features.