Difference between revisions of "Team:Edinburgh/Modeling"

 
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                       <li><a href="https://2015.igem.org/Team:Edinburgh/DNPBiosensor">DNP Biosensor</a></li>
 
                       <li><a href="https://2015.igem.org/Team:Edinburgh/DNPBiosensor">DNP Biosensor</a></li>
 
                       <li><a href="https://2015.igem.org/Team:Edinburgh/PMABiosensor">PMA Biosensor</a></li>
 
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                       <li><a href="https://2015.igem.org/Team:Edinburgh/CBD">Making it Stick</a></li>            
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                       <li><a href="https://2015.igem.org/Team:Edinburgh/CBD">Making it Stick</a></li>            
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                       <li><a href="https://2015.igem.org/Team:Edinburgh/Results">Results</a></li>
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                       <li><a href="https://2015.igem.org/Team:Edinburgh/Results">Limits of Detection</a></li>
 
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                   <li><a href="https://2015.igem.org/Team:Edinburgh/MedalCriteria">Medal Criteria</a></li>   
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                   <li><a href="https://2015.igem.org/Team:Edinburgh/MedalCriteria">Accomplishments</a></li>   
 
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<h2>Overview</h2>
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This year we focused our modeling efforts on the development of our device design.
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We worked on reaction-diffusion systems which helped us to find the weak points in our designs and to come up with new prototypes.
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                    <h2 class="section-heading">Coming soon</h2>
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The model consists of two main parts; diffusion and reaction. The diffusion part predicts how the solution, once applied, will move through the paper and the reaction part models how the different enzymes and chemicals present on the paper will react with each other.
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<h2>The Base Conditions</h2>
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The starting conditions of the model are made by using a png image import which defines the different parts of the biosensor i.e.: where the solution is applied, hydrophobic areas, frontiers and where the enzymes are freeze dried.
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<h2>Diffusion-reaction </h2>
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A diffusion kernel, along with a diffusion matrix, control the movement of the solution on paper and form the backbone of the diffusion model. Our “world” is updated at every time step which, in turn, updates the concentration on every point of the paper.
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At every time step we also use a list of the reaction rates to update the model with changing concentrations. We use vector calculus throughout the code to make efficient use of resources.
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      <p>
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<a href="https://github.com/aseemnarang17/Classafied-modelling"> Go to code</a>
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Latest revision as of 19:11, 20 November 2015

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Modeling

Overview

This year we focused our modeling efforts on the development of our device design. We worked on reaction-diffusion systems which helped us to find the weak points in our designs and to come up with new prototypes.

The model consists of two main parts; diffusion and reaction. The diffusion part predicts how the solution, once applied, will move through the paper and the reaction part models how the different enzymes and chemicals present on the paper will react with each other.

The Base Conditions

The starting conditions of the model are made by using a png image import which defines the different parts of the biosensor i.e.: where the solution is applied, hydrophobic areas, frontiers and where the enzymes are freeze dried.

Diffusion-reaction

A diffusion kernel, along with a diffusion matrix, control the movement of the solution on paper and form the backbone of the diffusion model. Our “world” is updated at every time step which, in turn, updates the concentration on every point of the paper. At every time step we also use a list of the reaction rates to update the model with changing concentrations. We use vector calculus throughout the code to make efficient use of resources.

Go to code