Difference between revisions of "Team:Calgary/Software"

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<h3>★  ALERT! </h3>
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<p>This page is used by the judges to evaluate your team for the <a href="https://2019.igem.org/Judging/Medals">medal criterion</a> or <a href="https://2019.igem.org/Judging/Awards"> award listed below</a>. </p>
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<p> Delete this box in order to be evaluated for this medal criterion and/or award. See more information at <a href="https://2019.igem.org/Judging/Pages_for_Awards"> Instructions for Pages for awards</a>.</p>
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                    <h1 class="page-title">Software</h1>
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<h1>Software</h1>
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                    <h1>Software Tools</h1>
<h3>Best Software Tool Special Prize</h3>
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                </div>
<p>Regardless of the topic, iGEM projects often create or adapt computational tools to move the project forward. Because they are born out of a direct practical need, these software tools (or new computational methods) can be surprisingly useful for other teams. Without necessarily being big or complex, they can make the crucial difference to a project's success. This award tries to find and honor such "nuggets" of computational work.
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                <p>
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                    To help the iGEM community, and synthetic biology communit as a whole, iGEM Calgarybuilt two software tools for the iGEM competition. One to optimize BioBricks for synthesis,
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                    and the other to help develop genetic algorithms.
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                </p>
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                <p>
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                    BOTs was shown to be compatible with synthesis checking software such as IDT Gene Fragment Synthesis, can be easily used with its website to optimize BioBricks.
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                </p>
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                <p style="margin-bottom:5vh">
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                    iGAM is built within an R package, iGAM is flexible enough to allow teams to build their own genetic algorithms, iGAM is a toolbox.
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                </p>
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To compete for the <a href="https://2019.igem.org/Judging/Awards">Best Software Tool prize</a>, please describe your work on this page and also fill out the description on the <a href="https://2019.igem.org/Judging/Judging_Form">judging form</a>.
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                        <a target="blank" href="https://2019.igem.org/Team:Calgary/BOT">
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To be eligible, your software has to be documented and made available under an OSI approved open source license. You must also delete the alert box on the top of this page to be eligible for this prize.
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                                <img src="https://static.igem.org/mediawiki/2019/7/78/T--Calgary--BOTs-logo.png" width="50%" style="margin-left: auto; margin-right: auto; display: block;" />
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                                    <h3 style="text-align:center">BOTs</h3>
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                                    <p style="text-align:center">BioBrick Optimization Tool for synthesis</p>
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                                    <p>A tool created to help synthetic biologists synthesize BioBricks by removing repeats, optimize gc content, and optimize for expression.</p>
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<h3> Inspiration </h3>
 
<p>
 
Here are a few examples from previous teams:
 
</p>
 
<ul>
 
<li><a href="https://2016.igem.org/Team:BostonU_HW">2016 BostonU HW</a></li>
 
<li><a href="https://2016.igem.org/Team:Valencia_UPV">2016 Valencia UPV</a></li>
 
<li><a href="https://2014.igem.org/Team:Heidelberg/Software">2014 Heidelberg</a></li>
 
<li><a href="https://2014.igem.org/Team:Aachen/Project/Measurement_Device#Software">2014 Aachen</a></li>
 
</ul>
 
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                        <a target="blank" href="https://2019.igem.org/Team:Calgary/iGAM">
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                                <img src="https://static.igem.org/mediawiki/2019/a/ac/T--Calgary--iGAM.png" width="50%" style="margin-left: auto; margin-right: auto; display: block;" />
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                                    <h3 style="text-align:center">iGAM</h3>
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                                    <p style="text-align:center">international Genetic Algorithm Machine</p>
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                                    <p>Using Genetic Algorithms to understand and modify proteins for chosen parameters. This software tool was critical in creating modGIX a potentially more emulsion-resistant version of 6GIX.</p>
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                    <h4> <a href="https://2019.igem.org/Team:Calgary/Model">Software in Modelling</a></h4>
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                    <p>
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                        Not only creating software tools for the iGEM community, we developed multiple algorithms
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                        to help us understand our systems to both save time and optimize the processes.
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                        Notably we developed a
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                        <a href="https://2019.igem.org/Team:Calgary/Model/EmulsionPrediction">machine-learning algorithm to help us understand emulsions</a>
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                        , a core component of our project.
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                    </p>
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                    <h4> <a href="https://2019.igem.org/Team:Calgary/Human_Practices">Software to Help an Industry</a></h4>
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                    <p>
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                        Furthermore, our team's devotion to helping the canola industry led us to develop
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                        a <a href="https://2019.igem.org/Team:Calgary/Modelling/StandardizedSeedGrading">computer vision algorithm to help standardize canola seed grading</a>.
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                    </p>
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                    <p>
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                        We also developed a <a href="https://2019.igem.org/Team:Calgary/SunnyDays">long-term weather forecasting system using machine-learning</a>.
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                    </p>
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{{Calgary/Footer}}

Latest revision as of 04:38, 14 December 2019

Software

Software Tools

To help the iGEM community, and synthetic biology communit as a whole, iGEM Calgarybuilt two software tools for the iGEM competition. One to optimize BioBricks for synthesis, and the other to help develop genetic algorithms.

BOTs was shown to be compatible with synthesis checking software such as IDT Gene Fragment Synthesis, can be easily used with its website to optimize BioBricks.

iGAM is built within an R package, iGAM is flexible enough to allow teams to build their own genetic algorithms, iGAM is a toolbox.

Software in Modelling

Not only creating software tools for the iGEM community, we developed multiple algorithms to help us understand our systems to both save time and optimize the processes. Notably we developed a machine-learning algorithm to help us understand emulsions , a core component of our project.

Software to Help an Industry

Furthermore, our team's devotion to helping the canola industry led us to develop a computer vision algorithm to help standardize canola seed grading.

We also developed a long-term weather forecasting system using machine-learning.