Difference between revisions of "Team:NCTU Formosa/Modeling"

In the modeling part, we discover optimum protein production time.

Firstly, we use hill-function based model:

In order to find the optimum parameters of, we use the genetic algorithm in Matlab. We want to characterize the actual kinetics of this Hill-function based model that accurately reflects protein production time. To achieve this purpose, we need to focus on the tasks of estimating model parameters from the experimental data in the case of hill-function based model for parameter inference. These reverse engineering tasks offer focus of the present difficulty, also known as the Estimation of Model Parameters Challenge.

When we have the simulated protein production rate, the graph of protein production versus time can be drawn (Fig.1) (Fig.2) (Fig.3). Thus, we can find the optimum protein production time Compared with the simulated protein production rate of time, our experiment data quite fit the simulation.

Figure 1. From this graph, the protein expression reaches peak after growing about 18 hours. This means that the E. Cotector can have maximum efficiency at this point.



Figure 2. From this graph, the protein expression reaches peak after growing about 15 hours. This means that the E. Cotector can have maximum efficiency at this point.



Figure 3. From this graph, the protein expression reaches peak after growing about 16 hours. This means that the E. Cotector can have maximum efficiency at this point.