Team:csu_china

Overview

Sweet guard aims to help as many diabetic patients as possible to get rid of the pain in the future. Helping users understand its working principle is an essential work. For another, corroborating the reliability of the experiment design is also necessary. Therefore, we build the Cellular automata Based Gene Circuit Visualization model and the dynamic ODE model respectively to meet these needs.

1. What is CA(Cellular automata) based gene circuit visualization? What is the importance of it?

2. CA models are often aimed at helping readers understand and are difficult to validate experimental data. How can CABGCV respect the experimental results on the basis of ensuring readability?

Based on the quantitative logic among parametric particles in synthetic biology, we use p5.js(oriented from processing) to quantitatively analyze the quantitative indicators and display them on the dashboard. Click for the CA model interface.

3. How to characterize the gene circuit by using mathematical terms?

4. What is the functional significance of ODE?

To Validate the experimental data by calculating ODE, which can assist us in quantitatively analyzing the experimental results and predicting the product performance under multiple conditions.

5. How do we fit and determine parameters?

In the process of selecting specific equations to verify the experimental data, we determine the parameter approximation by constant transformation processing and fractional function fitting to the original data set to be substituted into the original solution of ODE.

References

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[3] Xie, M. et al. β-cell-mimetic designer cells provide closed-loop glycemic control. Science (New York, N.Y.) 354, 1296–1301 (2016).
[4] Ausländer, D. et al. A synthetic multifunctional mammalian pH sensor and CO2 transgene-control device. Molecular cell 55, 397–408 (2014).
[5] Watson, E. M., Chappell, M. J., Ducrozet, F., Poucher, S. M. & Yates, J. W. T. A new general glucose homeostatic model using a proportional-integral-derivative controller. Computer Methods and Programs in Biomedicine 102, 119–129 (2011).
[6] Baggio, L. L. & Drucker, D. J. Biology of Incretins: GLP-1 and GIP. Gastroenterology 132, 2131–2157 (2007).
[7] Cheung, A. T. et al. Glucose-dependent insulin release from genetically engineered K cells. Science 290, 1959–1962 (2000).