Team:Tsinghua-A/Team
In biological world, when information flows through gene-regulatory networks, it may cause noise. Through the information theory, we use modeling computation and wet lab work to realize biological significance of recurring parallel designs in nature. Therefore, we combined the research theory of biology and automation. We are composed of 2 students from department of biology and 11 students from department of automation. Different from the other teams, because most of us are from department of automation, our project has a lot to do with information theory. We use the knowledge of probability theory, information theory, cybernetics, and so on to predict and verify the experiment. Not only most of our experiments verified the theory, but the predict is almost the same with our experiment result. Compared to other teams who use biological experiments to finish the actual operation and practical application, we focus on realizing the knowledge about life world, which is more like theory research. Both application and theory research are the two important keys in biological research. Our work is divided into experiment, modeling computation, human practice, web page, etc. Following is our members and works:
Inspiration
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What should this page contain?
- Include pictures of your teammates, don’t forget instructors and advisors!
- You can add a small biography or a few words from each team member, to tell us what you like, and what motivated you to participate in iGEM.
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