Awards
On this page, we would like to show you in detail the standards of medals we have met and why we met them.
Gold Medal
Integrated Human Practices
We have demonstrated how we have integrated the investigated issues into the purpose, design, and
execution of our project. From the visit to Huaheng BioTech, we aimed at making an FBA tool to make
predictions more efficiently. And from lots of Human Practices works, we have upgraded our design many
times, gradually making it a perfect project. We have documented our process and described how HP works
informed and shaped our project at different stages.
Improve a Previous Project
We have improved the function of existing iGEM projects:
1. Biobricks Recommendation
We spent lots of time and managed to design a new algorithm based on key-words extraction and behavior analysis. This robust algorithm allows our system to search Biobricks after getting users' models. We implemented this based on the database of UESTC-Software 2018, who developed many Biobricks-related algorithms but didn't implement it.
2. Platform Simplification
Different from the other iGEM-Software computing projects, Alpha-Ant, for instance, did not have any convenient ways to share users' findings when using the software. We developed a simple sharing function with which users can easily share their models with partners to do scientific research more efficiently.
And different from many iGEM-Software projects, we do not use a complicated friend system to make our share function more concise and efficient.
And different from many iGEM-Software projects, we do not use a complicated friend system to make our share function more concise and efficient.
Model our Project
Our design and implementation are based on the insight we gained from modeling. And we used four main models as follows for an overview.
1. FBA FVA and rFBA!
Flux Balance Analysis (FBA) is a mathematical method for simulating metabolism in metabolic networks. It is based on linear programming to calculate fluxes when the model is stable. And Flux Variability Analysis (FVA) is an extension of FBA. It can show the minimum and maximum range of each reaction flux while they satisfy constraints and have the same optimal objective by solving a double linear programming problem.
Not only can ForeSyn support FBA and FVA, it can also support rFBA, which is a more accurate way of analysis! The word rFBA stands for regulatory FBA, which adds boolean regulatory network in the original metabolic network to make the solution space more constrained, and thus get more precise output. We read the paper and get data from iMC1010v1-v2, and then edit the Gene-Reaction Rules to optimize the networks.
Not only can ForeSyn support FBA and FVA, it can also support rFBA, which is a more accurate way of analysis! The word rFBA stands for regulatory FBA, which adds boolean regulatory network in the original metabolic network to make the solution space more constrained, and thus get more precise output. We read the paper and get data from iMC1010v1-v2, and then edit the Gene-Reaction Rules to optimize the networks.
2. Object-Relational Mapping
Object-Relational Mapping (ORM) enables us to work with databases more comfortable and safer. It fills the gap between object-oriented programming languages and relational databases and avoids the vulnerability of SQL Injection. In practice, we use Django ORM with MySQL backend to provide fast, flexible, and reliable service.
3. Message Queues
Our website requires computing large models, and it is quite embarrassing to see users waiting for browsers for so long. So we use message queues to maintain computing tasks. In this way, we split computing models from websites, which can offer a much better experience.
Demonstration of our work
We have shown that our system works correctly on the Demonstration page. Not only that, we have done several validation works documented on the Results page. All of these show our software useful in the real world, which is the most significant aim we think iGEM software projects should achieve.
Silver Medal
Validated Contribution
We have done many validation works to make sure that our software works. We collected several cases of the real-world in different papers and got the same predictions using our project. And we have provided thorough documentation of the process of validation on our wiki.
Collaborations
This year we have significantly worked with many currently registered 2019 iGEM teams in a meaningful way:
With UESTC-Software:
Since our project is based on the databases and UESTC-Software had done a great job in optimizing databases and giving information in detail clearly, we collaborated with them. We get their cleaned data and built our recommendation algorithms on it. After giving recommended Biobricks, our list would link the Biobricks back to their information pages, respectively.
With SYSU:
In June, we visited SYSU and had a meeting with their iGEM team members. We communicated with our team projects and gave helpful suggestions to each other. They offered us useful advice on accuracy issues in our project and helped us to make a change of project emphasis.
With USTC:
The USTC team is the other team of our school, which focuses on biology, and most of their members majored in biology. Therefore, we communicate a lot throughout the whole project. For example, they have taught us the usage of COBRA, tested our project, and gave useful advice, and we together conducted a 4-day experimental training in the lab to help more students to use our tools.
Human Practices
We have thought carefully about whether our work is responsible and good for the world. For one thing, our work would benefit many researchers of factories and labs by allowing them to do pre-analysis before modify their methods of experiments very efficiently. For another, our project will enable researchers to find a more environmentally friendly way of production without cutting down productivity.
We investigated these issues with our PI, professors from our university, and Mrs. Lei, a lecture giver in CCiC, who was very concerned about the ethical questions about biology. And we have documented theses works in detail on the Human Practices page.
We investigated these issues with our PI, professors from our university, and Mrs. Lei, a lecture giver in CCiC, who was very concerned about the ethical questions about biology. And we have documented theses works in detail on the Human Practices page.
Bronze Medal
Registration and Giant Jamboree Attendance
We have registered as a software team, and we will attend the exciting Giant Jamboree!
Competition Deliverables
We have completed our Wiki, Poster, Judging Form, and we will give a dramatic presentation!
Attributions
With great appreciation, we have described what work our team did and what other people did for our project on the Attributions page.
Project Inspiration and Description
Our project began with a visit to a local factory, and we have documented it on the Description page. Also, we have described how we achieve our goals and gave a comparison among existing alike tools to show how our project extraordinarily useful.
Contribution
As a software team, we have made a new substantial contribution to the iGEM community: Biobricks Recommendation.
We spent lots of time and finally managed to design a new algorithm based on key-words extraction and behavior analysis used for searching Biobricks after a customized model built by the user. It can inform the user Biobricks he can use by giving a list of Biobricks, in which elements are linked to the respective pages of BioMaster 2.0, the project developed by UESTC-software.
And we have provided thorough documentation of how it works on our team wiki.
We spent lots of time and finally managed to design a new algorithm based on key-words extraction and behavior analysis used for searching Biobricks after a customized model built by the user. It can inform the user Biobricks he can use by giving a list of Biobricks, in which elements are linked to the respective pages of BioMaster 2.0, the project developed by UESTC-software.
And we have provided thorough documentation of how it works on our team wiki.