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<meta charset="utf-8"> | <meta charset="utf-8"> | ||
− | <title> | + | <title>Code Book</title> |
<link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-menu&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | <link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-menu&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | ||
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<link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-background-layer-bottom&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | <link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-background-layer-bottom&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | ||
<link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-background-banner&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | <link href="https://2018.igem.org/wiki/index.php?title=Template:NEFU_China/CSS-background-banner&action=raw&ctype=text/css" rel="stylesheet" type="text/css"> | ||
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<style> | <style> | ||
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margin-top: 0px; | margin-top: 0px; | ||
margin-left: 0px; | margin-left: 0px; | ||
+ | } | ||
+ | #menu li ul li:hover ul{ | ||
+ | background:rgba(0,0,0,0.75)!important; | ||
+ | } | ||
+ | li#mainlevel_01 a { | ||
+ | color: #FFE5B5!important; | ||
+ | |||
+ | } | ||
+ | li#mainlevel_01 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_02 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_02 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_03 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_03 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_05 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_05 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_06 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_06 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_07 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_07 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | li#mainlevel_08 a { | ||
+ | color: #FFE5B5!important; | ||
+ | } | ||
+ | li#mainlevel_08 a:hover { | ||
+ | font-size:30px!important; | ||
+ | text-shadow:0px 0px 8px #FFE5B5, | ||
+ | 0px 0px 42px #FFE5B5, | ||
+ | 0px 0px 72px #FFE5B5, | ||
+ | 0px 0px 150px #FFE5B5; | ||
+ | } | ||
+ | #menu li ul li ul li a:hover { | ||
+ | color: rgba(0,223,252,1); | ||
+ | border-top: dotted 1px rgba(255,255,255,0.91); | ||
+ | border-bottom: dotted 1px rgba(255,255,255,0.91); | ||
+ | background: rgba(0,223,252,.02); | ||
+ | } | ||
+ | #nav .mainlevel a { | ||
+ | color: black; | ||
+ | text-decoration:none; | ||
+ | line-height:32px; | ||
+ | display:block; | ||
+ | padding:0 5px; | ||
+ | font-size: 25px!important; | ||
+ | font-family: 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji' !important; | ||
+ | } | ||
+ | .layer-bottom { | ||
+ | z-index: -2; | ||
+ | position: absolute; | ||
+ | margin-top: 36px!important; | ||
} | } | ||
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<body> | <body> | ||
<!--menu--> | <!--menu--> | ||
− | <div id="menu" style="background-color: | + | |
− | <li id="nav">           | + | <div id="menu" style="background-color:rgba(0,0,0,1.0)!important"> |
− | + | <li id="nav" style="left: 8%!important; width: 100%!important;">           | |
+ | |||
<ul class="firstmenu" style="float: left"> | <ul class="firstmenu" style="float: left"> | ||
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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> | ||
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Description" target="_self">DESCRIPTION | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Description" target="_self">DESCRIPTION & DESIGN</a></li> |
− | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Coding book" target="_self">CODE BOOK</a></li> | |
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Coding book" target="_self"> | + | |
</ul> | </ul> | ||
</li> | </li> | ||
− | |||
− | |||
<li class="mainlevel" id="mainlevel_03"> | <li class="mainlevel" id="mainlevel_03"> | ||
− | <a href="https://2018.igem.org/Team:NEFU_China/ | + | <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"> | ||
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− | |||
− | |||
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<li><a href="https://2018.igem.org/Team:NEFU_China/Lock_Key" target="_self">LOCK & KEY</a></li> | <li><a href="https://2018.igem.org/Team:NEFU_China/Lock_Key" target="_self">LOCK & KEY</a></li> | ||
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Suicide" target="_self"> | + | <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> | + | <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> | ||
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Notebook" target="_self"> | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Basic_Part" target="_self">BASIC PARTS</a></li> |
+ | <li><a href="https://2018.igem.org/Team:NEFU_China/Composite_Part" target="_self">COMPOSITE PARTS</a></li> | ||
+ | <li><a href="https://2018.igem.org/Team:NEFU_China/Improve" target="_self">IMPROVEMENT PARTS</a></li> | ||
+ | <li><a href="https://2018.igem.org/Team:NEFU_China/Part_Collection" target="_self">PARTS COLLECTION</a></li> | ||
+ | <hr> | ||
+ | <li><a href="https://2018.igem.org/Team:NEFU_China/Notebook" target="_self">NOTEBOOK</a></li> | ||
<li><a href="https://2018.igem.org/Team:NEFU_China/Protocol" target="_self">PROTOCOL</a></li> | <li><a href="https://2018.igem.org/Team:NEFU_China/Protocol" target="_self">PROTOCOL</a></li> | ||
</ul> | </ul> | ||
</li> | </li> | ||
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<li class="mainlevel" id="mainlevel_05"> | <li class="mainlevel" id="mainlevel_05"> | ||
<a href="https://2018.igem.org/Team:NEFU_China/Model"><img id="model" src="https://static.igem.org/mediawiki/2018/0/0c/T--NEFU_China--_MODEL.png">MODEL</a> | <a href="https://2018.igem.org/Team:NEFU_China/Model"><img id="model" src="https://static.igem.org/mediawiki/2018/0/0c/T--NEFU_China--_MODEL.png">MODEL</a> | ||
<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> | ||
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Model1" target="_self"> | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Model1" target="_self">CORRESPONDING COEFFICIENT</a></li> |
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Model2" target="_self"> | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Model2" target="_self">KILLING MODEL</a></li> |
</ul> | </ul> | ||
</li> | </li> | ||
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<ul id="sub_06"> | <ul id="sub_06"> | ||
<li><a href="https://2018.igem.org/Team:NEFU_China/Software" target="_self">OVERVIEW</a></li> | <li><a href="https://2018.igem.org/Team:NEFU_China/Software" target="_self">OVERVIEW</a></li> | ||
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Software1" target="_self"> | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Software1" target="_self">CODING</a></li> |
− | <li><a href="https://2018.igem.org/Team:NEFU_China/Software2" target="_self"> | + | <li><a href="https://2018.igem.org/Team:NEFU_China/Software2" target="_self">MISLEADING</a></li> |
+ | <li><a href="https://2018.igem.org/Team:NEFU_China/Software3" target="_self">WORDSEGMENT</a></li> | ||
</ul> | </ul> | ||
</li> | </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> | ||
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</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"> | ||
+ | <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> | </div> | ||
<div id="banner"> | <div id="banner"> | ||
− | <img src="https://static.igem.org/mediawiki/2018/ | + | <img src="https://static.igem.org/mediawiki/2018/c/c0/T--NEFU_China--coddebook.png" alt="banner" id="banner-img"> |
</div> | </div> | ||
+ | <div class="layer-bottom"> | ||
+ | |||
+ | <canvas id="canvas" style="background:#000000"></canvas> | ||
+ | |||
+ | <script type="text/javascript"> | ||
+ | |||
+ | window.onload = function(){ | ||
+ | var canvas = document.getElementById("canvas"); | ||
+ | var context =canvas.getContext("2d"); | ||
+ | var W = window.innerWidth; | ||
+ | var H = 7400; | ||
+ | //var H = window.innerHeight*1.5; | ||
+ | canvas.width = W; | ||
+ | canvas.height = H; | ||
+ | var fontSize = 20; | ||
+ | var colunms = Math.floor(W /fontSize); | ||
+ | var drops = []; | ||
+ | for(var i=0;i<colunms;i++){ | ||
+ | drops.push(0); | ||
+ | } | ||
+ | |||
+ | |||
+ | var str1 = "ATCG"; | ||
+ | var str2 = "01"; | ||
+ | function draw(){ | ||
+ | context.fillStyle = "rgba(0,0,0,0.2)"; | ||
+ | context.fillRect(0,0,W,H); | ||
+ | context.font = "700 "+fontSize+"px 微软雅黑"; | ||
+ | context.fillStyle = "#003544"; | ||
+ | for(var i=0;i<colunms/2;i++){ | ||
+ | var index = Math.floor(Math.random() * str1.length); | ||
+ | var x = i*fontSize; | ||
+ | var y = drops[i] *fontSize; | ||
+ | context.fillText(str1[index],x,y); | ||
+ | if(y >= canvas.height){ | ||
+ | drops[i] = 0; | ||
+ | } | ||
+ | if(Math.random() > 0.99){ | ||
+ | drops[i] = 0; | ||
+ | } | ||
+ | drops[i]++; | ||
+ | } | ||
+ | for(var i=colunms/2;i<colunms;i++){ | ||
+ | var index = Math.floor(Math.random() * str2.length); | ||
+ | var x = i*fontSize; | ||
+ | var y = drops[i] *fontSize; | ||
+ | context.fillText(str2[index],x,y); | ||
+ | if(y >= canvas.height){ | ||
+ | drops[i] = 0; | ||
+ | } | ||
+ | if(Math.random() > 0.99){ | ||
+ | drops[i] = 0; | ||
+ | } | ||
+ | drops[i]++; | ||
+ | } | ||
+ | }; | ||
+ | |||
+ | function randColor(){ | ||
+ | var r = Math.floor(Math.random() * 256); | ||
+ | var g = Math.floor(Math.random() * 256); | ||
+ | var b = Math.floor(Math.random() * 256); | ||
+ | return "rgb("+r+","+g+","+b+")"; | ||
+ | } | ||
+ | |||
+ | draw(); | ||
+ | setInterval(draw,60); | ||
+ | }; | ||
+ | |||
+ | </script> | ||
+ | |||
+ | |||
+ | |||
+ | </div> | ||
+ | |||
<div id="background-content"> | <div id="background-content"> | ||
− | <h1> | + | <h1 style="font-size: 65px;color: orange!important;height: 84px;padding-top: 11px;">Code Book</h1> |
<p> | <p> | ||
− | + | In English text, each letter has a certain frequency. We constructed a list of letter frequencies for each letter. Also, in living organisms, each codon is used with a certain frequency. Based on this relationship between English letters and codons, we find out the correspondence between letters and codons by using DFS (Depth First Search) algorithm and optimization arithmetic.<br> | |
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</p> | </p> | ||
− | < | + | <br> |
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− | + | <h1 style="font-size: 45px;color: orange!important;line-height: 40px;">Create a letter-frequency table and a codon-frequency table</h1> | |
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<p> | <p> | ||
− | + | According to the literature, we obtain the information of the frequency of letters and codons. | |
+ | <br> | ||
+ | letter frequency table:<br> | ||
+ | <img src="https://static.igem.org/mediawiki/2018/9/9c/T--NEFU_China--letter-freq.png" style="width:900px;"><br> | ||
+ | codon frequency table:<br> | ||
+ | <img src="https://static.igem.org/mediawiki/2018/d/d6/T--NEFU_China--codon-freq.png" style="width:900px;"><br> | ||
+ | |||
</p> | </p> | ||
− | < | + | |
− | < | + | <br> |
+ | <br> | ||
+ | <hr> | ||
+ | |||
+ | <br> | ||
+ | <h1 style="font-size: 45px;color: orange!important;line-height: 40px;">Find out the correspondence between letters and codons by using DFS Algorithm</h1> | ||
<p> | <p> | ||
− | + | We build up a tree structure where the codons and the frequency of the codons are stored on each node. Then we use the depth-first search algorithm to traverse down from the root node successively, and match condon-frequence with the letter- frequency to obtain the correspondence between letters and codons.<br> | |
+ | The tree structure is shown as bellow.<br> | ||
+ | <br> | ||
+ | <div align="center"> | ||
+ | <img src="https://static.igem.org/mediawiki/2018/5/57/T--NEFU_China--s1-tree.png" style="width:600px;"></div><br> | ||
+ | |||
+ | |||
</p> | </p> | ||
<br> | <br> | ||
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<br> | <br> | ||
− | <h1> | + | <h1 style="font-size: 45px;color: orange!important;line-height: 40px;">Get the optimal solution by using optional algorithm.</h1> |
<p> | <p> | ||
− | + | In step 2, we get the correspondence between letters and codons. But some letters have multiple corresponding relationships. For example, in figure 1, the letters E and T correspond to codons GAU, GCU, GAA, E and T also correspond to codons GAU, GCU, AUG. What’s more, the letter T can also correspond to codons GAU, GCU, GCA. Therefore, we use the optimal algorithm to determine one of the multiple correspondence. <br> | |
<br> | <br> | ||
+ | For example (letter T):<br> | ||
+ | <br> | ||
+ | <div align="center"> | ||
+ | <img src="https://static.igem.org/mediawiki/2018/8/8f/T--NEFU_China--s1-analys.png" style="width:600px;"></div><br> | ||
+ | |||
</p> | </p> | ||
− | < | + | <br> |
− | + | <hr> | |
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− | + | <h1 style="font-size: 65px;color: orange!important;">RESULTS</h1> | |
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<p> | <p> | ||
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− | + | Print the correspondence between letters and codons: | |
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− | + | <div align="center"> | |
− | + | <img src="https://static.igem.org/mediawiki/2018/2/25/T--NEFU_China--codebook_table.png"></div> | |
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Latest revision as of 01:52, 18 October 2018
Code Book
In English text, each letter has a certain frequency. We constructed a list of letter frequencies for each letter. Also, in living organisms, each codon is used with a certain frequency. Based on this relationship between English letters and codons, we find out the correspondence between letters and codons by using DFS (Depth First Search) algorithm and optimization arithmetic.
Create a letter-frequency table and a codon-frequency table
According to the literature, we obtain the information of the frequency of letters and codons.
letter frequency table:
codon frequency table:
Find out the correspondence between letters and codons by using DFS Algorithm
We build up a tree structure where the codons and the frequency of the codons are stored on each node. Then we use the depth-first search algorithm to traverse down from the root node successively, and match condon-frequence with the letter- frequency to obtain the correspondence between letters and codons.
The tree structure is shown as bellow.
Get the optimal solution by using optional algorithm.
In step 2, we get the correspondence between letters and codons. But some letters have multiple corresponding relationships. For example, in figure 1, the letters E and T correspond to codons GAU, GCU, GAA, E and T also correspond to codons GAU, GCU, AUG. What’s more, the letter T can also correspond to codons GAU, GCU, GCA. Therefore, we use the optimal algorithm to determine one of the multiple correspondence.
For example (letter T):
RESULTS
Print the correspondence between letters and codons: