Difference between revisions of "Team:NEFU China/Software"

 
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#Software-content h1 {
 
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<ul id="sub_02">
 
<ul id="sub_02">
 
<li><a href="https://2018.igem.org/Team:NEFU_China/Background" target="_self">BACKGROUND</a></li>
 
<li><a href="https://2018.igem.org/Team:NEFU_China/Background" target="_self">BACKGROUND</a></li>
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<li><a href="https://2018.igem.org/Team:NEFU_China/Description" target="_self">DESCRIPTION</a></li>
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<li><a href="https://2018.igem.org/Team:NEFU_China/Description" target="_self">DESCRIPTION &amp; DESIGN</a></li>
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<li><a href="https://2018.igem.org/Team:NEFU_China/Design" target="_self">DESIGN</a></li>
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<li><a href="https://2018.igem.org/Team:NEFU_China/Coding book" target="_self">CODE BOOK</a></li>
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<li><a href="https://2018.igem.org/Team:NEFU_China/Coding book" target="_self">CODING BOOK</a></li>
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  </ul>
 
  </ul>
 
  </li>
 
  </li>
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<li class="mainlevel" id="mainlevel_03">
 
<li class="mainlevel" id="mainlevel_03">
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  <a href="https://2018.igem.org/Team:NEFU_China/Experiment"><img id="parts" src="https://static.igem.org/mediawiki/2018/6/62/T--NEFU_China--_RESULTS.png">EXPERIMENT</a>
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  <a href="https://2018.igem.org/Team:NEFU_China/Demonstrate"><img id="parts" src="https://static.igem.org/mediawiki/2018/6/62/T--NEFU_China--_RESULTS.png">EXPERIMENTS</a>
 
  <ul id="sub_03">
 
  <ul id="sub_03">
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Lock_Key" target="_self">LOCK &amp; KEY</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Lock_Key" target="_self">LOCK &amp; KEY</a></li>
−
  <li><a href="https://2018.igem.org/Team:NEFU_China/Suicide" target="_self">SUICIDE</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Suicide" target="_self">INFORMATION DESTRUCTION</a></li>
−
  <li><a href="https://2018.igem.org/Team:NEFU_China/Splicing" target="_self">SPLICING</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Splicing" target="_self">Pre-RNA SPLICING</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Demonstrate" target="_self">DEMONSTRATE</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Demonstrate" target="_self">DEMONSTRATE</a></li>
 
  <hr>
 
  <hr>
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  <ul id="sub_05">
 
  <ul id="sub_05">
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Model" target="_self">OVERVIEW</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Model" target="_self">OVERVIEW</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Model1" target="_self">MODEL1</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Model1" target="_self">CORRESPONDING COEFFICIENT</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Model2" target="_self">MODEL2</a></li>
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Model2" target="_self">KILLING MODEL</a></li>
 
  </ul>
 
  </ul>
 
  </li>
 
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Attributions" target="_self">ATTRIBUTIONS</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Attributions" target="_self">ATTRIBUTIONS</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Members" target="_self">MEMBERS</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Members" target="_self">MEMBERS</a></li>
−
 
−
  <li><a href="https://2018.igem.org/Team:NEFU_China/Sponsoring" target="_self">SPONSORING</a></li>
 
 
  </ul>
 
  </ul>
 
  </li>
 
  </li>
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  <a href="https://2018.igem.org/Team:NEFU_China/Human_Practices"><img id="humanpractice" src="https://static.igem.org/mediawiki/2018/9/91/T--NEFU_China--_HUMANPRACTICE.png">HUMAN PRACTICE</a>
 
  <a href="https://2018.igem.org/Team:NEFU_China/Human_Practices"><img id="humanpractice" src="https://static.igem.org/mediawiki/2018/9/91/T--NEFU_China--_HUMANPRACTICE.png">HUMAN PRACTICE</a>
 
  <ul id="sub_08">
 
  <ul id="sub_08">
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  <li><a href="https://2018.igem.org/Team:NEFU_China/Human_Practices" target="_self">OVERVIEW</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Gold_integrated" target="_self">GOLD INTEGRATED</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Gold_integrated" target="_self">GOLD INTEGRATED</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Silver" target="_self">SILVER</a></li>
 
  <li><a href="https://2018.igem.org/Team:NEFU_China/Silver" target="_self">SILVER</a></li>
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<div class="flexslider">
 
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  <li style="background-image: url(https://static.igem.org/mediawiki/2018/c/c0/T--NEFU_China--coddebook.png);">
 
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<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 1:</a></span>
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<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software1">Software 1:</a></span>
 
<span class="date">Coding</span>
 
<span class="date">Coding</span>
 
 
 
</p>
 
</p>
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  <h1>Build Coding Book.</h1>
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<h1>By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons.</h1>
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  <h1>Coding</h1>
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<h1>Build Coding Book.</h1>
 
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  </div>
 
  </div>
 
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  </li>
 
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  <li style="background-image: url(https://static.igem.org/mediawiki/2018/0/08/T--NEFU_China--enhance_password_image.png);">
 
  <div class="overlay"></div>
 
  <div class="overlay"></div>
 
  <div class="container">
 
  <div class="container">
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</p>
 
</p>
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  <h1>Enhance password security.</h1>
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  <h1>Misleading</h1>
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<h1>We added random sequences, introns, and enzymes to the codon sequences so that the intercepted codon information would not be easily decoded.</h1>
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<h1>Enhance password security.</h1>
 
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  <li style="background-image: url(https://static.igem.org/mediawiki/2018/d/da/T--NEFU_China--wordsegment_image.png);">
 
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  <div class="overlay"></div>
 
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  <p class="meta">
 
  <p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3:</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3:</a></span>
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<span class="date">English Word Segment</span>
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<span class="date">Word Segment</span>
 
 
 
</p>
 
</p>
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  <h1>Segment English Sentences without Spaces.</h1>
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  <h1>Word Segment</h1>
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<h1>Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results. </h1>
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<h1>Segment English Sentences without Spaces.</h1>
 
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<h1>Software</h1>
 
<h1>Software</h1>
 
<p>
 
<p>
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We develop the Encrypt & Decrypt software. By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons. The heart of our software is the Misleading module. By adding enzymes and introns to genes, we complicate the sequences and increase the security of our Coding Book. During the decryption period, we use regular expressions to match useless enzymes and introns, eliminating them and converting the rest of codons into letters. What’s more, we write the information of codons and letters into the picture as a qr code and users can scan the qr code to get this information.<br>
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We developed the Encrypt & Decrypt software. Using DFS (Depth First Search) algorithm and optimization arithmetic, we discovered the correspondence between English letters and DNA codons for amino acids. The key part of our software is the Misleading Module. Through adding introns into DNA sequence containing the transmitted information, we can complicate the DNA sequence and increase the security levels of our Code Book. During the decryption process, we use regular expressions to match useless introns, eliminate them and convert codons of the rest RNA sequences into letters. In addition, we can integrate the information codons and letters into the image of a quick responsive (QR) code. This will allow the receptor to scan the QR code and quickly retrieve the information. <br></p>
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            We also develop English Word Segmentation software. Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results.  
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<p>
 +
We developed English Word Segmentation software. Firstly, we implement word graph scanning based on prefix tree structure and construct DAG (Directed Acyclic Graph) to obtain all English word segmentation information. Secondly, we use an IF-IDF (Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation information.<br>
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<div class="blog-entry">
 
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<a href="https://2018.igem.org/Team:NEFU_China/Software1"><img src="https://static.igem.org/mediawiki/2018/8/88/T--NEFU_China--software1-small.png" class="img-responsive" alt="html5 bootstrap template"></a>
 
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<a href="https://2018.igem.org/Team:NEFU_China/Software2"><img src="https://static.igem.org/mediawiki/2018/0/08/T--NEFU_China--enhance_password_image.png" class="img-responsive" alt="html5 bootstrap template"></a>
 
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<a href="https://2018.igem.org/Team:NEFU_China/Software3"><img src="http://39.105.74.74/yellow.png" class="img-responsive" alt="html5 bootstrap template"></a>
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<a href="https://2018.igem.org/Team:NEFU_China/Software3"><img src="https://static.igem.org/mediawiki/2018/d/da/T--NEFU_China--wordsegment_image.png" class="img-responsive" alt="html5 bootstrap template"></a>
 
</div>
 
</div>
 
<div class="desc">
 
<div class="desc">
 
<p class="meta">
 
<p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3</a></span>
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<span class="date">English Word Segment</span>
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<span class="date">Word Segment</span>
 
 
 
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<script type="text/javascript" src="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/JavaScript-main-software&amp;action=raw&amp;ctype=text/javascript"></script>
 
<script type="text/javascript" src="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/JavaScript-main-software&amp;action=raw&amp;ctype=text/javascript"></script>
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<h1>Userfull links</h1>
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<h2>
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<a href="https://2018.igem.org/Team:NEFU_China">Home</a>
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&nbsp;&nbsp;&nbsp;
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<a href="https://2018.igem.org/Team:NEFU_China/Model">Model</a>
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                        &nbsp;&nbsp;
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                        <a href="https://2018.igem.org/Team:NEFU_China/Description">Project</a>
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&nbsp;&nbsp;
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<a href="https://2018.igem.org/Team:NEFU_China/Software">Software</a>
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    </h2>
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<h2>
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<a href="https://2018.igem.org/Team:NEFU_China/Basic_Part">Parts</a>
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&nbsp;&nbsp;&nbsp;&nbsp;
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<a href="https://2018.igem.org/Team:NEFU_China/Members">Teams</a>
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&nbsp;
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<a href="https://2018.igem.org/Team:NEFU_China/Lock_Key">Results</a>
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&nbsp;
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<a href="https://2018.igem.org/Team:NEFU_China/Notebook">Notebook</a>
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                        &nbsp;&nbsp;
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</h2>
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<h2>
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<a href="https://2018.igem.org/Team:NEFU_China/Human_Practices">Human &nbsp;Practice</a>
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<td style="padding-left: 70px">
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<h1>Follow us</h1>
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<img alt="facebook" src="https://static.igem.org/mediawiki/2018/b/b5/T--NEFU_China--facebook.png">
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&nbsp;&nbsp;&nbsp;
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        <img alt="twitter" src="https://static.igem.org/mediawiki/2018/3/36/T--NEFU_China--twitter.png">
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&nbsp;&nbsp;&nbsp;
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<img alt="wehchat" src="https://static.igem.org/mediawiki/2018/c/ca/T--NEFU_China--wechat.png">
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        <br>
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        <img alt="facebook" src="https://static.igem.org/mediawiki/2018/b/b5/T--NEFU_China--facebook.png">
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&nbsp;&nbsp;&nbsp;
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        <img alt="twitter" src="https://static.igem.org/mediawiki/2018/3/36/T--NEFU_China--twitter.png">
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&nbsp;&nbsp;&nbsp;
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<img alt="wehchat" src="https://static.igem.org/mediawiki/2018/c/ca/T--NEFU_China--wechat.png">
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<td style="padding-left: 70px">
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<h1>Contact us</h1>
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<h3>iGEM-NEFU_China2018</h3>
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<h3>Email: hexinglu@nefu.edu.cn</h3>
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<h3>No.26 Hexing Road, Xiangfang <br>District, Harbin, Heilongjiang <br>Province 150000</h3>
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Latest revision as of 02:06, 18 October 2018

Software Overview

Software

We developed the Encrypt & Decrypt software. Using DFS (Depth First Search) algorithm and optimization arithmetic, we discovered the correspondence between English letters and DNA codons for amino acids. The key part of our software is the Misleading Module. Through adding introns into DNA sequence containing the transmitted information, we can complicate the DNA sequence and increase the security levels of our Code Book. During the decryption process, we use regular expressions to match useless introns, eliminate them and convert codons of the rest RNA sequences into letters. In addition, we can integrate the information codons and letters into the image of a quick responsive (QR) code. This will allow the receptor to scan the QR code and quickly retrieve the information.

We developed English Word Segmentation software. Firstly, we implement word graph scanning based on prefix tree structure and construct DAG (Directed Acyclic Graph) to obtain all English word segmentation information. Secondly, we use an IF-IDF (Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation information.

html5 bootstrap template

Software 1 Coding

Build Coding Book.

By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons.

html5 bootstrap template

Software 2 Misleading

Enhance password security.

We added random sequences, introns, and enzymes to the codon sequences so that the intercepted codon information would not be easily decoded.

html5 bootstrap template

Software 3 Word Segment

Segment English Sentences without Spaces.

Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results.