Modelling

Modeling as an iterative process: The design-build-test cycle

One of the core aspects of synthetic biology is the iterative design-build-test-learn cycle, where the information gained from one experiment is used to design the subsequent experiments.

Within the learn stage of the design-build-test cycle, models can be used as a way to interpret data, and, more crucially, make predictions about the system that can be used in the design stage of the cycle. Modeling is itself an iterative process, where the predictions from the model are used in experiments. Constraints on time have put a limit on the number of iterations of the design-build-test cycle that we could perform. However, by using modelling we have been able to make predictions on how the expressed proteins of our biobricks would behave in an experimental setting. Furthermore, we have been able to feed the model with some data extracted from our own experiments.

In our project, we had two different modelling objectives:

1. To apply enzyme kinetics in order to predict the optimum amount of time for the blood-sample to be in contact with our ScAvidin-linker-LacZ part (BBa_2355313), or in other words, the incubation time.
2. To apply enzyme kinetics in order to predict the optimum amount of time for the blood-sample to be in contact with our ScAvidin- linker-LacZ part (BBa_2355313), or in other words, the incubation time.

1. Coffee
2. Tea
3. Milk