Team:NCTU Formosa/Demonstrate
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Demonstration
With months of hard work, our project has finally turn into reality. Now, let us demonstrate to you our project – E.Phoenix. A powerful, novel, and easy-comprehensive mutagenicity detecting system. The demonstration of the project features three parts:
1. Mutagenicity Bioassay
2. Mutagenicity Prediction AI
3. Detector EP & Visualizer EP
Mutagenicity Bioassay
Figure 1: Model simulation of different mutation rate / The growth curve of ydfD with different dose of EtBr
We first simulated our modified gene circuit design with Matlab. Moreover, we experimented with induced suicide protein and coupled with different concentrations of EtBr. As you can see in figure2, the higher the concentration, the faster the bacteria grow back. The simulated growth curve model prediction and wet lab experiment curve show the same curve tendencies. Therefore the experimental data were fitted with the growth curve formula and garnered the mutation rate.
Figure 2: Linear correlation of mutation rate in EtBr concentration (ydfD)
By organizing the experiment and computational growth model, the linear correlation of the Mutation rate in EtBr concentration owned a correlation coefficient of 0.962, which indicated the trustworthiness and credibility of our model and the mutagenic bioassay platform.
Detector EP
The following video will show how Detector EP works. Also, it demonstrates its two major composites, the cultivation section, and O.D. sensing section.
Mutagenicity Prediction AI
Figure 3: Mutagenicity prediction model user interface
The screenshot above showcased our user interface developed for our mutagenicity prediction AI. Interested? Just click the link below, and it will lead it to our mutagenicity prediction AI.
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Visualizer EP
Figure 4: Visualizer EP user interface
Besides, we also constructed the Visualizer EP, a racecar game that is linked to mutagenicity calculated and predicted by our computational growth model and mutagenicity prediction AI. Curious about how it works? Then take a look in the video below and check it out.
IoTtalk
Throughout E. Phoenix, you may be concerned about how we connect every part of our project so quickly. The answer is IoTtalk, a user-friendly IoT system. With the Arduino Yun board, we connected Detector EP, Visualizer EP, computational growth model, and mutagenicity prediction AI together.
Figure 5: IoTtalk
The project we have done this year is a complete system that can be fully used as an education module with hardware, biosensors, and software. The interconnection between these parts and its individual completeness enables us to moreover carry on this project into a further application for the detection of potential mutagens and promotion of awareness.
