Difference between revisions of "Team:Washington/Modeling"

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<h2> Modeling</h2>
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<h2> Modeling </h2>
  
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<p> In our project we developed a novel paper microfluidic device for accomodating two biological detection systems. Both for the paper device and the apatazyme detection system, we constructed computational models to provide a theoretical framework for our experimental findings.</p>
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<h4>Note</h4>
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<p>In order to be considered for the <a href="https://2015.igem.org/Judging/Awards#SpecialPrizes">Best Model award</a>, you must fill out this page.</p>
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<p> To model the functionality of the paper device, we developed a spatial model for fluid forces on a strip of paper and implemented it in COMSOL. The model simulates the material properties of the paper used in our experiments – represented by a rectangular prism – while submerged in fluid. We were able to calculate the magnitude of the fluid forces on the paper over time, which allowed insights on the influence of fluid forces on the device’s structural integrity. </p>
  
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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<p> For the aptazyme system, we constructed a time-dependent ODE model for protein expression resulting from an aptazyme-based genetic pathway.[1] It describes the level of protein expression over time as a function of various system parameters, including transcription, aptazyme folding and cleavage, translation and degradation of RNA fragments and proteins. </p>
  
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<p> We implemented the model in Python (using Tellurium [2]) and theoretically predicted results for various conditions. A comparison with literature data indicated a good fit between the computational model and the experimental setting. </p>
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Here are a few examples from previous teams:
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li>
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<h2> References </h2>
  
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<p> [1] Carothers JM et. al. (2011): Model-Driven Engineering of RNA Devices to Quantitatively Program Gene Expression; Science, vol. 334(6063), pp. 1716-1719 </p>
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<p> [2] Tellurium. Python enviroment for Systems Biology developed and maintained at UW Seattle. (http://tellurium.analogmachine.org) </p>
  
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Revision as of 00:59, 17 September 2015



Modeling

In our project we developed a novel paper microfluidic device for accomodating two biological detection systems. Both for the paper device and the apatazyme detection system, we constructed computational models to provide a theoretical framework for our experimental findings.

To model the functionality of the paper device, we developed a spatial model for fluid forces on a strip of paper and implemented it in COMSOL. The model simulates the material properties of the paper used in our experiments – represented by a rectangular prism – while submerged in fluid. We were able to calculate the magnitude of the fluid forces on the paper over time, which allowed insights on the influence of fluid forces on the device’s structural integrity.

For the aptazyme system, we constructed a time-dependent ODE model for protein expression resulting from an aptazyme-based genetic pathway.[1] It describes the level of protein expression over time as a function of various system parameters, including transcription, aptazyme folding and cleavage, translation and degradation of RNA fragments and proteins.

We implemented the model in Python (using Tellurium [2]) and theoretically predicted results for various conditions. A comparison with literature data indicated a good fit between the computational model and the experimental setting.

References

[1] Carothers JM et. al. (2011): Model-Driven Engineering of RNA Devices to Quantitatively Program Gene Expression; Science, vol. 334(6063), pp. 1716-1719

[2] Tellurium. Python enviroment for Systems Biology developed and maintained at UW Seattle. (http://tellurium.analogmachine.org)