Document

Medal Criteria

Gold Medal

Integrated Human Practices

We created a complete ‘advise-test-feedback-promote’ circle to improve our project. According to this 7-steps circle, we do our human practice corresponding to every step of it. Not only interviews and feedback were participated but conferences and meet-ups were attended. Meanwhile, we designed a Bio-Chess with both board game and online version to promote public engagement. Please see Human Practice for more details.

Model

Model plays an important role in the project. For database integration, we build a model to screen the blast results, which influences the reliability of our database directly. We used JS divergence for feature extraction and innovatively employed logistic regression classifier with polynomial features to classify blast results, which performed pretty well. For promoter prediction, we used machine learning method to construct promoter classifier. Then, we constructed multiple classifier system to improve the performance. With large-scale search model, we can identify promoter in a large-scale sequence. In a word, without model, there will be no BioMaster. Please see Model for more details.

Demonstrate

We bring BioMaster to this year’s Giant Jamboree. It’s an integrated biobrick database. In order to show clearly that this database can work under realistic conditions, we recorded a video. At the same time, we sent our database to some synthetic biologists and iGEM teams to solve their problems and they gave us their feedback.Meanwhile, we consulted lawyer for the intellectual property issues and made sure of the safety of our projects. Please see Demonstrate for more details.

Silver Medal

Validated Contribution

To accomplish the intended function, we well-designed the project and validated our project through wet-lab experiments. Via the results of our model and some specific examples to demonstrate that our project can peform our intended function. It was clearly documented on the wiki about how we achieve our goal in Design, Model. Please see Validation for more details.

Collaboration

We interacted with several iGEM teams. UESTC-China helped us verify our promoter prediction. We shared experience on database designing with NKU_CHINA,UESTC-China,USTC-Software. USTC-Software and us also tested each other's software prject and gave some feecbacks and technical supports. Please see Collaborations for more details.

Human Practice

To ensure our database is user-friendly enough, we communicated to many scholars, professors and engineers about their opinions on our project and we teamed up with Sichuan Technology and Science Museum to hold an iGEM day ‘Gene Go’. Please see Human Practice for more details.

Bronze Medal

Register for iGEM and attend

We have signed up for the collegiate category as in software track team. Certainly, we had a great summer for our joint effort and are going to attend the Giant Jamboree.

Deliverables: 1# Wiki 2#Poster 3#Presentation 4#Judging form

We have completed Wiki, poster, judging form and prepared a wonderful presentation for the final competition.

Attribution

Many people have supported our project and offered help. We documented every effort they made for us. Please see our Attributionsfor more details.

Contribution

We integrated eight traditional biological research databases to bring more cpmprehensive information to iGEMers and synthetic biologists. Also, several retrieval methods are provided. To promote synthetic biology, we designed Bio-Chess with a board game version and an online version. Please see our Contributionfor more details.

Special Awards

Best Integrated Human Practices

At the beginning of this competition, we came up with idea of constructing the database. Because of the specialty of our project, we serve mainly with iGEMers and synthetic biologists. We created a 7 step ‘advice-test-feedback-promoter’ circle to make sure our product is of well-used for synthetic biology. So, we integrated all our human practices in correspondence to every step of this circle including interview, questionnaire, communication and conference. We also collected their feedback and further improve our project. After all these work, we promoted the product to public and synthetic biologists in order to help them solve their problems. What’s more we designed Bio-Chess based on the simple procedure of gene engineering, with the integration of knowledge in a game, it affects public in a subtle way. Please see Integrated HP for more details.

Best Education & Public Engagement

We believe public engagement is important for us, iGEM and synthetic biology, so we deliberately devided public into 3 level—public, children and pre-iGEMer. We designed a Bio-Chess with both a board game and an online version. It was designed on the simple basis of genetic engineering. People can collect endonuclease and other substances and they may lose what they’ve already earned. To sitmulate children’s interest, we held ‘Gene Go’ with a series of activities such as cell structure fabrication to allow them to paticipate. Meanwhile, we organized a vivid children stage show ‘Cellulose Go’. For pre-iGEMers, the 1st iGEM Festival was held in UESTC, after games and some introduction, high school students showed strong will to join us. Please see Education & Engagement for more details.

Best Model

We are the best choice of the best model. We spend a lot of time and energy to construct our models, which played an important role in both parts of our project. For database integration, an essential work is to screen the blast results, which influences the reliability of our database directly. The most used thresholding method was proved to be unusable here, hence, we used JS divergence for feature extraction and innovatively employed logistic regression classifier with polynomial features to classify blast results, which performed pretty well. For promoter prediction, we used machine learning method to construct promoter classifier. Then, we constructed multiple classifier system to improve the performance. With large-scale search model, we can identify promoter in a large-scale sequence. With these, we constructed a promoter prediction model that can be used in both of prokaryote and eukaryote, which benefit biologists to find more promoters. Please see Model for more details.

Best Product Design

BioMaster aims at solving problems in iGEM Registry with unclear feature description of biobricks, incomplete information and the lack of biobricks. BioMaster integrates 8 traditional biological research databases. Via this database, not only can iGEMers be inspired by previous project, but they can discover more comprehensive information of biobricks beyond iGEM Registry. To make the database more user-friendly, we specially designed 4 ways to search for biobricks according to synthetic biologists’ different needs. Besides, there is a more beautiful UI surface for user to experience. Except for what mentioned above, we also use machine learning to construct a promoter prediction tool and a promoter database predicted from E. coli genome to assist synthetic biologists to discover potential promoter. Please see Applied Design for more details.