Difference between revisions of "Team:BIT/Hardware"

 
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<li><a href="https://2016.igem.org/Team:BIT/Judging_Form" >Judging</a></li>
 
<li><a href="https://2016.igem.org/Team:BIT/Judging_Form" >Judging</a></li>
 
                 <li><a href="https://2016.igem.org/Team:BIT/Parts_Submission">Parts</a></li>
 
                 <li><a href="https://2016.igem.org/Team:BIT/Parts_Submission">Parts</a></li>
                 <li><a href="https://2016.igem.org/Team:BIT/HP/Silver">Attrievement</a></li>
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                 <li><a href="https://2016.igem.org/Team:BIT/HP/Silver">Achievement</a></li>
 
<li><a href="https://2016.igem.org/Team:BIT/Introduction">Team</a></li>
 
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<h2><br><br><br>Background</h2>
 
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<h2><br><br><br><br><br><br><br>Design</h2>
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<h2><br><br><br>Design</h2>
 
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<img src="https://static.igem.org/mediawiki/2016/0/01/BIT_Figure_System_Design.png " class="img-responsive" alt="...">
 
<img src="https://static.igem.org/mediawiki/2016/0/01/BIT_Figure_System_Design.png " class="img-responsive" alt="...">
 
<center> <font size="1px">Figure System Design</font></center> <br><br>
 
<center> <font size="1px">Figure System Design</font></center> <br><br>
<p>
 
Firstly, the raspberry-pi can get the value of fluorescence(also some other values). Then it will send these data to the application through the Bluetooth serial port. After that the application will make analysis. Finally, it will show intuitive data with several graphs and charts. In addition, users can get their sports data such as the distance they have walked and physiology such us heart rate as well. What will impress the users is the user interface. We will make a professional, friendly and avant-garde UI to give users a fantastic using experience.<br><br>
 
</p>
 
 
<p>
 
<p>
 
Our device is designed for cultivating and detecting simples on standard 96-well plate. For offering the appropriate environment of bacterial growth, a constant temperature environment must be established inside our device. Meanwhile, in order to provide an accurately quantitative detection of disease markers, cultivation time must be control. Both the temperature and cultivation time can be set by users through the interface of our hardware. We also provide default setting for specific engineering bacteria so users can start the process conveniently. The setting information will be sent to Arduino, the lower microcontroller, for temperature control. In temperature control part, we use DS18B20 as temperature sensor and heating coil as heat source, together they constitute a closed loop multi-point temperature measurement and control system. Besides, fan and air circulation path also integrated inside our instrument, ensuring temperature consistency. In order to guarantee temperature stability and heating efficiency, we use mainstream PID temperature control algorithm for temperature control. after temperature reach its target, Raspberry Pi will start to calculate the incubation time in background. Once reach the pre-set time, our device will move on to detection part.<br><br>
 
Our device is designed for cultivating and detecting simples on standard 96-well plate. For offering the appropriate environment of bacterial growth, a constant temperature environment must be established inside our device. Meanwhile, in order to provide an accurately quantitative detection of disease markers, cultivation time must be control. Both the temperature and cultivation time can be set by users through the interface of our hardware. We also provide default setting for specific engineering bacteria so users can start the process conveniently. The setting information will be sent to Arduino, the lower microcontroller, for temperature control. In temperature control part, we use DS18B20 as temperature sensor and heating coil as heat source, together they constitute a closed loop multi-point temperature measurement and control system. Besides, fan and air circulation path also integrated inside our instrument, ensuring temperature consistency. In order to guarantee temperature stability and heating efficiency, we use mainstream PID temperature control algorithm for temperature control. after temperature reach its target, Raspberry Pi will start to calculate the incubation time in background. Once reach the pre-set time, our device will move on to detection part.<br><br>
 
</p>
 
</p>
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<img src="https://static.igem.org/mediawiki/2016/4/4e/BIT_Figure_Temperature_Control_Part.png" class="img-responsive" alt="...">
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<center> <font size="1px">Figure Temperature Control Part</font></center><br><br>
 
<p>
 
<p>
For the health part, we use Android API to access the health application. We can drive the data we want, then the application can make these to a graph or a chart. Because many applications such as WeChat, Whatapps, Facebook etc. can access the data in health, this part is feasible.<br><br>
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The detection part consists of GFP brightness detection part and sliding table. CMOS camera are used as brightness detection and blue laser LED as excitation light source. Mobile platform, driven by stepper motors, can move the multi-well plate to achieve point-by-point detection.<br><br>
 
</p>
 
</p>
 
<p>
 
<p>
A appealing user interface has a great attraction to customers. This application will use some superb UI segments with professional layout. The main color and shape of UI will fit in our other design such as Wiki, handout, poster. We will apply some special effect, gestures to catch up with the user interface in iOS system.<br><br>
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The CMOS camera is fixed in the upper center of the instrument, above the multi-well plate. A light filter of 525nm is placed in fort of camera, filters out the excitation light. Camera captures the image and sends it to Raspberry Pi, which performs the image processing. And finally the fluorescence intensity will be calculated based on picture brightness and exposure time.<br><br>
 
</p>
 
</p>
 
 
 
 
 
 
 
 
 
<div class="row text-center">
 
<h2><br><br><br><br><br><br><br>Result</h2>
 
<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
 
</div>
 
 
<p>
 
<p>
<b>1. Welcome Page</b><br>
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In order to meet the requirements of power consumption and excitation efficiency, we choose a blue laser LED with a wavelength of 475 nm as the excitation light source. The LED are fixed beside the camera, with an adjustable bracket for correction, making sure it is facing the target simple. Excitation light source is control by Raspberry Pi through relay switch, only light up when capturing images for saving energy.
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<br><br>
 
</p>
 
</p>
 
<p>
 
<p>
When we start the application for the first time, we can see these four welcome pages and they will show us the specialty and function of the software.
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Mobile platform consists of two sliding tables, providing degree of freedom in both XY directions. Sliding table is composed of stepper motor and screw and rail. Motor move the platform by rotating screw, provide with positioning accuracy of 0.1 mm. the control of sliding table is implemented by Arduino, which is always waiting Raspberry Pi sending the number of the sample. Once it gets the number, it will drive the mobile platform to the right position for camera detection.
 
<br><br>
 
<br><br>
 
</p>
 
</p>
 
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<img src="https://static.igem.org/mediawiki/2016/8/85/BIT_Figure_Fluorescence_Detection_Part.png" class="img-responsive" alt="...">
 
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<center> <font size="1px">fluorescence detection part</font></center><br><br>
 
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<center> <font size="1px">Figure. Welcome Pages</font></center>
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<p>
 
<p>
<b>2. Login page</b><br>
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After our instrument finish detection part, preliminary data will be showed at the 5-inch touch panel. User can control the instrument or access information of progress through the screen. Besides, users can use mobile app to download the detection results and read the detailed report on it.
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<br><br>
 
</p>
 
</p>
<p>
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<img src="https://static.igem.org/mediawiki/2016/4/43/BIT_Table_Module_Information_of_Hardware.png" class="img-responsive" alt="...">
After each start, there will be a login page. For old users, they will input their name and password. For new users, they will register a new account. If we forget our password, don't worry, we can find it by answering the  two questions we set in the registration.<br><br>
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<center> <font size="1px">Figure module information of hardware</font></center><br><br>
</p>
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<center> <font size="1px">Figure. Login page</font></center>
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<p>
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<b>3. Detection page</b><br>
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</p>
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<p>
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As the figure below, the application will first judge if the mobile phone is connected to Bluetooth and if it is paired with other devices. If not, then we will be reminded on the screen. After paring with others, the application can communicate with the paired devices, which means it can send or receive data. The data it received will show on the screen. We can cancel the connection by clicking the button.<br><br>
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</p>
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<center> <font size="1px">Figure. Detection page</font></center>
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<p>
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<b>4. UI design</b><br>
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</p>
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<p>
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Detection module:
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We use the vertical layout mode. In the above, we can see the basic information of the person, the organ in the graph is matched to the disease. The probability of having the disease is in below. Click the macro scope we can see the full report, which will tell you the result in detail, as well as the comparison to standard result. Click the download button we can save the result to local. By the way, doctors can use the report as reference.<br><br>
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</p>
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<p>
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Doctor module:
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We use the vertical layout. Through the filter above, we can get the doctor we want. Click the button, more information will show us. We can make online consultation with him. <br><br>
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</p>
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<p>
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Discover module:
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This part tries to popularize some general knowledge written by famous scientists or doctors in medicine to users.. We can make comment or like the article in below.<br><br>
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</p>
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<p>
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Personal module:
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It contains all information about ourselves such medical history, all earlier result, comment, settings etc.<br><br>
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</p>
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<p>
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<b>5 Core codes</b><br><br>
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</p>
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<center> <font size="1px">Figure. Main program codes of detection module</font></center>
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<center> <font size="1px">Figure. Main program codes of communication module</font></center>
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<center> <font size="1px">Figure. Main program codes of detection module layout</font></center><br><br>
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<div class="row text-center">
<h2><br><br><br><br><br><br><br>Discussion</h2>
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<h2><br><br><br>Result</h2>
 
<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
 
<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
 
</div>
 
</div>
<p>About the product:
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<img src="https://static.igem.org/mediawiki/2016/a/a2/BIT_Figure_Hardware_External_Design.png" class="img-responsive" alt="...">
This software is designed for community medical institute and family. Users use this application along with the detector can get the result convieniently. Unfortunately, the doctor module is an ideal module. Because the background of the medical system, that part cannot be used in daily life immediately. But we believe that mobile medical is a trend in the future. This module can be used sooner or later.<br><br>
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<center> <font size="1px">hardware design</font></center><br><br>
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<img src="https://static.igem.org/mediawiki/2016/3/38/BIT_Figure_Hardware_Internal_Design.png" class="img-responsive" alt="...">
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<center> <font size="1px">hardware internal design</font></center><br><br>
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<img src="https://static.igem.org/mediawiki/2016/2/24/BIT_Figure_Hardware_Exploded_View.png" class="img-responsive" alt="...">
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<center> <font size="1px">hardware exploded view</font></center><br><br>
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<div class="row text-center">
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<h2><br><br><br><br>Discussion</h2>
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<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
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</div>
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<p>
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Similar to last year, we provide a low cost and non-laboratory hardware solution for pre-disease detection. Different from last year’s project, we have integrated cultivation and detection functions on one instrument, and make it work automatically. As for detection sensor, we used CMOS camera with better linearity instead of the old monolithic photodiode, providing higher detection accuracy. And we used sliding table to build a point-by-point detection platform.<br><br><br>
 
</p>
 
</p>
 
<p>
 
<p>
About costumer:
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After our market research, we found that there are fewer instruments available on the market to meet the needs of biological disease detection, and most of these instruments have large volume and expensive price, which will impede large-area promotion. In contrast, our device are less costly and easier to use, more suitable for promotion.<br><br>
We designed a very friendly user interface, simple but doesn't lack of fashion. Users will have a comfortable using experience. Through a small scale test, this application got good evaluations.<br><br>
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</p>
 
</p>
<p><i>
 
'This software has a avant-garde style and full of science. The layout of the detection module is really creative. I love it very much.' --- A student in School of Information and Electronics
 
<br><br></i></p>
 
<p><i>
 
'The discover module is a brilliant point, for users can learn some basic knowledge while making self-detection. I think this application is also a precaution software. I will recommend this to my family.' --- A student in School of Life and Science
 
<br><br></i></p>
 
<p><i>
 
'Under the current background, this application can show us the future. Mobile health will be a vital treatment in few years. I am very proud that they can make a fantastic software like this.' --- A student in Life and Science
 
</font><br><br></i></p>
 
 
<p>
 
<p>
About Apps store:
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For other use such as in parts verification or other biosensor detection systems, our hardware also provides a convenient solution. User can change detecting fluorescence wavelength by change the light filter and the excitation light source. And the cultivation time and temperature settable too.
This application still needs to be modified. We believe that we can download it in the apps store in the future.<br><br>
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</p>
 
</p>
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<div class="row text-center">
<h2><br><br><br><br><br><br><br>Lab Note</h2>
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<h2><br><br><br>Lab Note</h2>
 
<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
 
<center><hr width="70%"  align="center"  color="#c91f77" size=1;></hr></center>
 
</div>
 
</div>
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<img src="https://static.igem.org/mediawiki/2016/4/4e/BIT_Table_Hardware_Notes.png" class="img-responsive" alt="..."><br><br><br><br><br>
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Latest revision as of 02:48, 20 October 2016

<!DOCTYPE html> Biology

PROJECT


HARDWARE








Abstract


Our hardware is an open source hardware solution for pre-cancer detection in non-laboratory environments, such as community hospitals. Engineering bacteria’s cultivation and detection were integrated in one machine, low cost and convenient operation make it has good potential for promotion, which solves the problem that current market lack of such kind of detecting instrument. The process of cultivation and detection and data analysis are all automatically, and the results will present to the user by sending to the user mobile phone through the Bluetooth or showing on the screen, so that users can easily access test results, which is highly readable. This device is developed based on Raspberry Pi3 open-source platform, which offers high scalability, and most of components are mainstream and easy purchasing on market. All the source code and design drawings are available for developers in our wiki. Besides, our hardware also can be widely used in parts verification and biosensor detection systems.




Background


Pre-disease detection based on our engineering bacteria, targeted at community hospitals and home, has its advantage. But detecting disease in biological methods requires some special instrument. For detecting fluorescent proteins, prevailing way is using ELISA instrument or similar device to measure the fluorescence intensity of the samples, then calculate fluorescent protein concentration. In addition to ELISA instrument, there are some there device like Quantitative Real-time PCR or immunofluorescence detector can also able to detect fluorescent protein. But all the instrument above are too expensive for large-area promotion, and are not specially design for disease detection, which limits the use of these instruments.




Design


...
Figure System Design


Our device is designed for cultivating and detecting simples on standard 96-well plate. For offering the appropriate environment of bacterial growth, a constant temperature environment must be established inside our device. Meanwhile, in order to provide an accurately quantitative detection of disease markers, cultivation time must be control. Both the temperature and cultivation time can be set by users through the interface of our hardware. We also provide default setting for specific engineering bacteria so users can start the process conveniently. The setting information will be sent to Arduino, the lower microcontroller, for temperature control. In temperature control part, we use DS18B20 as temperature sensor and heating coil as heat source, together they constitute a closed loop multi-point temperature measurement and control system. Besides, fan and air circulation path also integrated inside our instrument, ensuring temperature consistency. In order to guarantee temperature stability and heating efficiency, we use mainstream PID temperature control algorithm for temperature control. after temperature reach its target, Raspberry Pi will start to calculate the incubation time in background. Once reach the pre-set time, our device will move on to detection part.

...
Figure Temperature Control Part


The detection part consists of GFP brightness detection part and sliding table. CMOS camera are used as brightness detection and blue laser LED as excitation light source. Mobile platform, driven by stepper motors, can move the multi-well plate to achieve point-by-point detection.

The CMOS camera is fixed in the upper center of the instrument, above the multi-well plate. A light filter of 525nm is placed in fort of camera, filters out the excitation light. Camera captures the image and sends it to Raspberry Pi, which performs the image processing. And finally the fluorescence intensity will be calculated based on picture brightness and exposure time.

In order to meet the requirements of power consumption and excitation efficiency, we choose a blue laser LED with a wavelength of 475 nm as the excitation light source. The LED are fixed beside the camera, with an adjustable bracket for correction, making sure it is facing the target simple. Excitation light source is control by Raspberry Pi through relay switch, only light up when capturing images for saving energy.

Mobile platform consists of two sliding tables, providing degree of freedom in both XY directions. Sliding table is composed of stepper motor and screw and rail. Motor move the platform by rotating screw, provide with positioning accuracy of 0.1 mm. the control of sliding table is implemented by Arduino, which is always waiting Raspberry Pi sending the number of the sample. Once it gets the number, it will drive the mobile platform to the right position for camera detection.

...
fluorescence detection part


After our instrument finish detection part, preliminary data will be showed at the 5-inch touch panel. User can control the instrument or access information of progress through the screen. Besides, users can use mobile app to download the detection results and read the detailed report on it.

...
Figure module information of hardware





Result


...
hardware design


...
hardware internal design


...
hardware exploded view






Discussion


Similar to last year, we provide a low cost and non-laboratory hardware solution for pre-disease detection. Different from last year’s project, we have integrated cultivation and detection functions on one instrument, and make it work automatically. As for detection sensor, we used CMOS camera with better linearity instead of the old monolithic photodiode, providing higher detection accuracy. And we used sliding table to build a point-by-point detection platform.


After our market research, we found that there are fewer instruments available on the market to meet the needs of biological disease detection, and most of these instruments have large volume and expensive price, which will impede large-area promotion. In contrast, our device are less costly and easier to use, more suitable for promotion.

For other use such as in parts verification or other biosensor detection systems, our hardware also provides a convenient solution. User can change detecting fluorescence wavelength by change the light filter and the excitation light source. And the cultivation time and temperature settable too.




Lab Note


...




Message Board


iGEM is a Jamboree!


Wang Xu

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Kai, Web Geekster

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Jenn, Coders' Playground

Contact Us


Address

Beijing Institute of Technology,
No. 5 South Zhong Guan Cun Street,
Haidian Beijing 100081, P. R. China

Twitter : @igem_BIT

Sina Weibo : @igem_BIT

Website : http://www.bit.edu.cn