Difference between revisions of "Team:SJTU-BioX-Shanghai/Model"

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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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To complete for the gold medal criterion #3, please describe your work on this page and fill out the description on your <a href="https://2017.igem.org/Judging/Judging_Form">judging form</a>. To achieve this medal criterion, you must convince the judges that your team has gained insight into your project from modeling. You may not convince the judges if your model does not have an effect on your project design or implementation.
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                        <div class="my-title h5-my-responsive" id="section1">Overview</div>
  
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                        <p>Basically, we build two models generated by MATLAB in order to analyze and evaluate our synthetic biology system, and estimate concentrations of multiple inducers.</p>
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Please see the <a href="https://2017.igem.org/Judging/Medals"> 2017 Medals Page</a> for more information.  
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                        <div class="my-title h5-my-responsive" id="section2">Signal Pathway Model </div>
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                        <p>We constructed our signal pathway model and associated it with inducers, RNAs and proteins. We also modeled STAR and antiSTAR behavior in circuit.</p>
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</div>
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                        <p>We developed our circuit model in Simbiology (a toolkit in MATLAB) which allowed us to create real time simulations of how our circuit would behave, thus giving useful information for wet lab to optimize our assembly process. And by sensitivity analyses, we found important issues that could help us improve biosensor’s performance.</p>
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                        <div class="my-title h5-my-responsive" id="section3">Color Chart Model </div>
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                        <p>We also developed a tool which could create a inducer-color matching chart. </p>
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                        <p>This color chart could be either stored in our mobile APP or printed as a convenient inducer-color matching tool, by which we could easily quantify two kinds of inducers at the same time. This tool was developed in MATLAB by utilizing image processing methods.</p>
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To compete for the <a href="https://2017.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2017.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
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<h5> Inspiration </h5>
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                                Instruction
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Here are a few examples from previous teams:
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                        </a>
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<ul>
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<li><a href="https://2016.igem.org/Team:Manchester/Model">Manchester 2016</a></li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">TU Delft 2016  </li>
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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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</ul>
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                                Signal Pathway
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Latest revision as of 03:25, 2 November 2017

Overview
Overview

Basically, we build two models generated by MATLAB in order to analyze and evaluate our synthetic biology system, and estimate concentrations of multiple inducers.

Signal Pathway Model

We constructed our signal pathway model and associated it with inducers, RNAs and proteins. We also modeled STAR and antiSTAR behavior in circuit.

We developed our circuit model in Simbiology (a toolkit in MATLAB) which allowed us to create real time simulations of how our circuit would behave, thus giving useful information for wet lab to optimize our assembly process. And by sensitivity analyses, we found important issues that could help us improve biosensor’s performance.

Color Chart Model

We also developed a tool which could create a inducer-color matching chart.

This color chart could be either stored in our mobile APP or printed as a convenient inducer-color matching tool, by which we could easily quantify two kinds of inducers at the same time. This tool was developed in MATLAB by utilizing image processing methods.

Device
Instruction
Model
Signal Pathway