Team:USTC-Software

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<title>Project Description</title>
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    <title >  Home  USTC-Software</title>
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            <p class="h2">Map</p>
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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><a href="https://2012.igem.org/Team:USTC-Software/software.html#map" class="da-link">Read More</a>
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            <div class="da-img"><img src="https://static.igem.org/mediawiki/2012/3/37/USTC-Software-images-1.png" width="480px" height="330"/></div>
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            <p class="h2">Console</p>
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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><a href="https://2012.igem.org/Team:USTC-Software/software.html#console" class="da-link">Read More</a>
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            <p class="h2">SandBox</p>
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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><a href="https://2012.igem.org/Team:USTC-Software/software.html#sandbox" class="da-link">Read More</a>
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            <p class="h2">Report</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><a href="https://2012.igem.org/Team:USTC-Software/software.html#report" class="da-link">Read More</a>
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<div id = "description_title">Project Description</div>
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<div id = "description_team_name">USTC-Software 2012</div>
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<p/>This summer, USTC-Software team is going to combine experiment data, genetic circuits and mathematical models into a single software, one that not only enables us to better understand Genetic Regulatory Networks (GRNs), but also provide researchers with complete workflows.
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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 on a plasmid or with experimental data, but complete work that combines the three factors have not been paid enough attention to. Here we propose a project that aims to fully connect them with software that enables us to study GRNs in a much more efficient way.  
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<p/>The project starts from using experimental data to generate proper ordinary differential equations (ODEs) that describe the behavior of the given data. With ODEs, we can abstract the possible GRNs and use the Parts available in registry to generate plasmid models that can be used in experiments. In this way, we combine mathematics, biology and experiments, the three main areas supporting a complete iGEM project, in a single software.  
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        <div id="reverse_engineering" class="feature">
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            <div class="feature_right">
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                    <p class="h2">Reverse Engineering</p>
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                <div class="details">
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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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                <div class="more">
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                    <p><a href="https://2012.igem.org/Team:USTC-Software/project.html#reverse-engineering">Read More</a></p>
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                    <p class="h2">Genetic Regulatory Networks</p>
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                <div class="details">
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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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                <div class="more">
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                    <p><a href="https://2012.igem.org/Team:USTC-Software/project.html#grn">Read More</a></p>
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                    <p class="h2">All-in-one Software</p>
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                <div class="details">
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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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                </div>           
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                <div class="more">
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                    <p><a href="https://2012.igem.org/Team:USTC-Software/software.html#software_intro">Read More</a></p>
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                    <p class="h2">Machine Learning</p>
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                <div class="details">
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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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                <div class="more">
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                    <p><a href="https://2012.igem.org/Team:USTC-Software/project.html#machine-learning">Read More</a></p>
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{{Team:USTC-Software/global_footer}}

Latest revision as of 09:15, 9 August 2013

global_header

igem
Home USTC-Software

Map

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.

Read More

Console

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.

Read More

SandBox

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.

Read More

Report

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.

Read More

Reverse Engineering

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.

Read More

Genetic Regulatory Networks

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.

Read More

All-in-one Software

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.

Read More

Machine Learning

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.

Read More

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Sponsors

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