Huaheng Biotech is a company which is in the leading position around the world, in the field of alanine products producing using methods of microbiological fermentation. They had put a major capital investment in research and development. After communicating with their research leader, we took a visit to their plant and had a meetup with their researchers.
Despite their high level of research, they said that there remained no good pre-analytical way to decide how to improve their process of production. The existing way and tools had too many limits to be used by researchers so that they could only experiment with changes thought out of experience. Also, with careful consideration of environmental protection, they kept on finding ways to improve their products while not impact productive rates.

After acknowledging the problems faced in the real world, we went to have a meeting with our PI, professor Jiong Hong. Prof. Hong informed us about the existence of Flux Balance Analysis and further researches based on it. Then we had some investigation about FBA, only to find that all existing tools to do FBA lack the ease of use despite the beauty of its method. It first came into our mind to build a great FBA tool that meets the requirements of real production environments.

We proposed a revolutionary workflow that would greatly improve efficiency and decrease the complexity of using. In other words, we designed a high-level framework to automatically solve many inner logics and thus simplify the process of analysis.

We first considered to support a wild and customized searching function based on the optimization of databases. After a job done by UESTC-Software in 2018, we wanted to do some upgrade of the scale of databases.
Then we visited Wenfei Yu, the leader of team USTC in 2018, and got acknowledged about some common databases used in Syn-Biology and their shortcomings. Also, we became aware of cobrapy, a tool that offers several APIs to do FBA.
To help us, USTC 2019 team gave us a hand, which enabled us to be instantly familiar with cobra.

We went to Guangzhou in July and visited the iGEM team of Sun Yat-sen University. In the meetup, we introduced our projects to each other. At that time, we devoted ourselves to optimize our database which was at a great scale and then linking the output to FBA’s input. However, our idea hadn’t been fully approved by the SYSU team and their professor. They put forward that out idea about optimizing massive databases was not targeted for Synthetic Biology. In other words, there was a bias in our aim, for the work done to optimize the databases will distract us to design FBA workflow and its efficiency.
In the emergency meeting that night we all admitted that the problem did exist. Then we decided immediately a change of emphasis of our project, which would more concentrated on the optimization of FBA and the whole framework.

He helped us tease out our whole project and his clear thinking impressed us very much. He then raised a question that whether we can provide a recommendation of Biobricks when we end up giving graphs of analysis. For example, if modifications and analysis had been done to the user's model based on E. coli, the researcher can immediately be acknowledged by our system which Biobricks he or she can use. After more discussion, we found it would be a pretty useful function. So we decided to append our system with a micro recommendation system for proper Biobricks.

CCic, which stands for the Conference of China iGEMer Community, is the biggest synthetic biology conference in China. This year we had a wonderful time there in Shenzhen. We did presentations and our idea was evaluated by many experts and lovers in the field of synthetic biology. There we were encouraged to expand our project to a platform, using which users can share their models, and see the history of modifying. It enriched our project, made it closer to a mature one.

After our presentation, teammates of Tongji 2019 found us and asked whether we can offer some more specific suggestions, for their project was related to increasing generation rate of products of fermentation. After knowing that we can only analyze changes of major metabolites’ flux, they were quite disappointed. We talked to the professors and some senior students there at CCIC and they approved our design. For "it is not unnecessary for a researcher who does flux analysis to do this job, for it should be considered during experimental design. Your analysis of flux major metabolites is much more useful in a generative perspective and considering the accuracy."

During the communication with UESTC-Software 2019, we came up with the idea to build our recommendation system base on their well-handled data, for they had done a great job in collecting data and optimizing databases. We then reached cooperation with each other and the first time opened up collaboration lying deeply in the projects of iGEM Software Teams.

Team USTC has always been enthusiastic to help us test our tool and improve our project. We had done several tests together, during which some small functions, such as optimizations with the display of graphs in the output, comparisions between different but alike models and polishing UI of the interface, were added in.

unfinished yet