Team:SJTU-software/Design
Database
I. Sources
We discovered that iGEM's plant-based part list and other advisory information on plant synthetic biology have not been updated since 2016. At the same time, due to the incompleteness of the chassis data and the category data in the part data in the iGEM database, some iGEM part registry-based searches cannot accurately retrieve the part data that was once applied to the plant chassis. So, we decided to use method of crawler and the transcript for comparision to get the exact chassis the team used. We filter a large number of duplicate matches respective in the their wiki through python programs and bash programs, and select the exact information with the artificial selection.
We located all component of the biobrick used in 7 types of plants chassis and provide more detailed information, like the team's wiki and project's title.
Considering only the data that has been verified in the KEGG database lacks some predictive data content. At the same time, KEGG's plant page index is not clear enough, and there are some inconveniences in finding the unique metabolic pathways of each plant. While the sequence in PMN database is often not complete, there is a lack of information. We integrated the plant metabolite information from PMN, NCBI, TARI and KEGG database.
II. Structure
- Plant metabolite database
- Plant Biobrick database
III. Search
We use mysql to store our data. In the rear end, Java deals with the search process. And Django, a python web framework, is in charge of front-end interaction including sending http request and return the corresponding webpage.
We support fuzzy matching and multi-keyword search.In Metabolite Database, we offer key word search, fuzzy matching and multi-keyword search. Users can select the species they want and choose gene, enzyme,reaction, pathway, compound to search. They can also select "All" in the dropdown menu, and choose the information you want, simply input the keyword to search. In the PartData page, users can search the biobricks they want. We support fuzzy matching (except iGEM ID) and multi-keyword search. Users can choose description, category, type , iGEM ID or all to search. As for Plasmid Data, we offer name, purpose, publication, insertname and all to search.
Tools
We developed there type of tools: Prediction, Visulization and Network Modification.
I. Prediction
The Prediction tool is developed to predict the probability between the enzyme sequence and the substrate in photosynthetic carbon fixation with the complicated CNN model(Go to our Model wikipage for more detail).
It can be used to predict a directed mutated enzyme's relationship with a certain substrate, or to predict a new substrate in photosynthetic carbon fixation.
II. Visulization
We integrated the SMILES visualization plug-in in the iGEM team SJTU-software last year‘s project "Metlab" and added 3D SMILES visualization capability with adjustable options.
The user can input the smlies code to get a visualization, and the adjustment plug-in can be used for further refinement.
This tool obtains the API from Chembl and is completed with JavaScript. It is also integrated into our database and prediction display.
III. Modification
Phosyme contains information on the overall metabolic network, including the system biology markup format files for these species. These documents provide a model for the metabolic networks of these organisms.
To better help pathway design, Phosyme provides tools for metabolic network modification.With the help of our network modification tool can adjust their SBML format model online, deleting some part of this biological metabolic network model and export that in 5 types of format. It is also able to convert a SMBL shorthand format to a SBML format file or conversely.
Web Page
We choose Java as the backend programming language. Through script programed in Java, mysql is called and it can complete the accurate extraction, filtering and sorting of the data in the database, which makes the process of passing the background data to the front end accurate and reliable, and its frame structure is clear enough.
Django has been selected as our frontend frame, because its simple url method and clear structure. For static display, besides html, css, we refer to Bootstrap and apply some css plug-in components including Bootstrap-table, Bootstrap-select, Bootstrap-menu to make sure a practical layout. As for dynamic pages, JavaScript, jQuery and Ajax help us.
In the part of toolbox, we also used smiles-drawer designed by our team last year and api of chembl to establish our smiles-drawer. To modify sbml, we use Gemtract, a project of the department of systems biology and bioinformatics at the University of Rostock.
We use the Aliyun ECS server as our web server. The user accesses the public server and then forwards it to the private server through Aliyun to retrieve the resources from the private server.
Information
We designed the information manual to provide a brief introduction to the research content and achievements of plant synthetic biology. It provides two main information topics: Genetic level and Metabolic level, and explains plant synthetic biology research tools, databases and parts. In the process of information collection and production, we referred to the OpenPlant website and consulted relevant journals. Besides, we drew up the topic of the information manual by referring to the scientific research themes in the three International Conferences on Plant Synthetic Biology and Bioengineering.
3D Game
In order to promote synthetic biology and iGEM to the public, we developed a synthetic biology room escape game. Players can learn about synthetic biology in the game. In this interesting science manual, users can learn some basic knowledge about synthetic biology. And in the secret room escape game, the key to escape is to use these basic knowledge to solve the corresponding puzzles. We have promoted the game extensively in Shanghai Jiao Tong University, so that people from all walks of life have tried our games, especially non-biological students, and collected their feedback and opinions.In addition to promoting in the university, we also put our game videos and links on Bilibili and Youtube, hoping to use the network to promote our games and promote our software. Feedback can also be received in the comments section. In the future, we hope to change the game into a VR game and let more teenagers learn about synthetic biology and our software through this game.
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SJTU - software
