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

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

we use Hill-function based model :

In order to characterize the actual kinetics of this Hill-function based model that precisely reflects protein expression time, we use the genetic algorithm (GA) in MATLAB.

To achieve this, 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.

The optimum parameters which were calculated by GA can help us to simulate the optimum protein expression.

The graph of simulated protein expression versus time were drawn (Fig.1) (Fig.2) (Fig.3). Thus, we can find the optimum protein expression time compared with the simulated protein expression (orange curve), our experimental data (blue curve) quite fit the simulation.

Figure 1. 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 2. 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 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.