Team:USTC-Software

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    <title> USTC-Software Home</title>
 
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    <meta name="Description" content="Our teammates have designed a software to help the  synthetic biologists work more efficiently
 
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in the summer holiday.we enjoyed igem ,we enjoyed the competition ">
 
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                        <div class="camera_caption fadeFromBottom"><em>Take a gNAP before wearing your gloves!<br/>Genetic Network Analyze and Predict</em></div>
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<h1>Welcome to our wiki!</h1>
 
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                    <div data-thumb="https://static.igem.org/mediawiki/2013/9/9f/USTC-Software-main2s.jpg" data-src="https://static.igem.org/mediawiki/2013/1/15/2.jpg">
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                        <div class="camera_caption fadeFromBottom"><em>The sketch and final GUI of gNAP!</em></div>
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            <div class="camera_caption fadeFromBottom"> <em>USTC-Software —— The unicorn consists "USTC".</em> </div>
 
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            <div class="camera_caption fadeFromBottom"><em>Having discussion with iGEM Software co-head judge, Gil Alterovitz.</em></div>
 
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            <div class="camera_caption fadeFromBottom"> <em>Team members were working.</em>            </div>
 
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            <div class="camera_caption fadeFromBottom"> <em>What's your opinion?</em>            </div>
 
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            <div class="camera_caption fadeFromBottom"> <em>Come to see this ! ~</em>            </div>
 
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                        <div class="camera_caption fadeFromBottom"><em>We compare the result of our software with gene expression profile in literature.</em></div>
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                        <div class="camera_caption fadeFromBottom"><em>We are USTC-Software!</em></div>
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        <h1>Description</h1>
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        <p>Synthetic biology has been working on transforming target organisms, which usually means integrating new genes with an available network to achieve a high expression level of certain compounds. Nevertheless, the new-integrated genes are always not the original parts of the target metabolic network, so it is hard to predict how the new genes will affect the network. </p>
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<p align="justify">Gene Network Analyze and Predict (gNAP) is a software which can model and analyze the change of new GRN constructing after exogenous gene’s import. What’s more, gNAP's reverse analysis based on global GRN gives some advise to experimenters before choosing the imported gene meeting their purpose.</p>
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        <p>Our application aims to simulate genetic networks. The application analyzes the stability of genetic networks after introduction of exogenous genes. Meanwhile, given the original network and specific purposes, the application traces the regulative process back and gives possible regulative patterns.</p>
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        <h2>Abstract</h2>
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            <h3>Map</h3>
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            <p>Map is a simple and easy software to visualize your experimental data. Click to import the data and you will get exactly what you want.</p>
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            <h3>Genetic Regulatory Networks</h3>
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            <p>Genetic Regulatory Network(GRN) has been a major subject in recent researches of synthetic biology, and the modulation of a GRN gives rise to a variety of exciting works among iGEM programs as well as softwares assisting synthetic biology researches. Traditionally, researches of GRNs have been focused on either connecting GRNs with real parts in the registry or with experimental data. Therefore, we want to completely connect these three factors.</p>
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            <p>Report organizes all output information in folders. You can review the simulation result while looking at the behaviors of certain genes or proteins. In addition, Report creates a web page where you can review the results on the go.</p>
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<p align="justify"><span style="font-family:Arial, Helvetica, sans-serif;">gNAP, gene network analyze and predict, is our main software which could analyze the input gene’s effects forward and reversely. gFinder, gene finder, is a website software which could find a specific gene in a database by gene’s function of regulation. gRNA, gene regulatory network analysts, is a small game which could improve the children’s ability of network analysis.<br/></span></p>
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            <h3>Reverse Engineering</h3>
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            <p> Reverse Engineering is the process of discovering the inner technological or scientific principles of a device, object or system. Synthetic biology is a combination of biology and engineering, and with the engineering process gets more and more complicated, often it is impossible to easily understand the inside, which is the biological part of the system. Reverse engineering serves perfectly for the purpose to bring back the biological essence.</p>
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            <h3>Machine Learning</h3>
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            <p>Machine learning is a branch of artificial intelligence that is widely used in many disciplines such as software engineering, computer vision, finance, Neuroscience and bioinformatics. During reverse engineering, we use many machine learning techniques and algorithms to help optimize the process so that the process is faster and more accurate.</p>
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<h2>Methodologies</h2>
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            <p>In order to fully combine biological networks, experimental data and mathematical models, we build a suite of applications that serves to solve different tasks and make them work seamlessly together. With the all-in-one software suite, you can display experimental data, extract mathematical models, understand the genetic regulatory networks and get a well-designed report of the results. We designed the user interfaces to be fun to interact with and easy to use.</p>
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<p align="justify">In order to simulate the GRN’s working and analyze the changing after exogenous gene imported, some advanced algorithms and classical methods are employed in the software. These algorithms and methods include Binary Tree method, Needle-Wunsch Algorithm, Decision Tree method, Hill Equation and PSO Algorithm.</p>
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            <div id="ash_container"><h3>Console</h3>
 
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                  <p>Console is where you manage heavy computing and complex tasks. With different buttons controlling each parameter, you can optimize the behaviors of the software. We applied evolution algorithm and machine learning techniques in the network inferences to provide the best simulation of your data.</p>
 
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                              <div><span><a href=" ">Read More</a></span></div>
 
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            <div id="ash_container"><h3>Sand Box</h3>
 
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                        <p>SandBox displays the Genetic Regulatory Networks in a clean and interactive way, with clear connection and 3-D interaction, you will get better understanding of how genes and proteins regulating each other.</p>
 
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                              <div><span><a href="">Read More</a></span></div>
 
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<p align="justify">Our team hope to create a better community for iGEM software, so we <a href="https://2013.igem.org/Team:USTC-Software/collaboration" id="homelink">collaborate</a> with other teams. Open source on github with detailed <a href="https://2013.igem.org/Team:USTC-Software/Project/Develop" id="homelink">API</a> of our source code make our software’s development more easy and convenient. What’s more, to <a href="https://2013.igem.org/Team:USTC-Software/Human_practice" id="homelink">popularize</a> iGEM in our campus, we also give “Hi” from iGEM to all the students and teachers and give their “Hello” back.</p>
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     <a href="http://www.ustcif.org/default.php"><img src='https://static.igem.org/mediawiki/2012/d/d9/USTC-Software-images-ustcif-logo.png' /></a>
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Latest revision as of 14:26, 7 November 2013

Header2

Slide

Take a gNAP before wearing your gloves! Genetic Network Analyze and Predict
The sketch and final GUI of gNAP!
We compare the result of our software with gene expression profile in literature.
We are USTC-Software!

Home

Overall

Gene Network Analyze and Predict (gNAP) is a software which can model and analyze the change of new GRN constructing after exogenous gene’s import. What’s more, gNAP's reverse analysis based on global GRN gives some advise to experimenters before choosing the imported gene meeting their purpose.

Software

gNAP, gene network analyze and predict, is our main software which could analyze the input gene’s effects forward and reversely. gFinder, gene finder, is a website software which could find a specific gene in a database by gene’s function of regulation. gRNA, gene regulatory network analysts, is a small game which could improve the children’s ability of network analysis.

Methodologies

In order to simulate the GRN’s working and analyze the changing after exogenous gene imported, some advanced algorithms and classical methods are employed in the software. These algorithms and methods include Binary Tree method, Needle-Wunsch Algorithm, Decision Tree method, Hill Equation and PSO Algorithm.

Communication

Our team hope to create a better community for iGEM software, so we collaborate with other teams. Open source on github with detailed API of our source code make our software’s development more easy and convenient. What’s more, to popularize iGEM in our campus, we also give “Hi” from iGEM to all the students and teachers and give their “Hello” back.

Sponsors

Retrieved from "http://2013.igem.org/Team:USTC-Software"