Team:Freiburg/Model


Modeling

Modeling

In synthetic biology, modeling can be applied to a wide range of topics, for example modeling of genetic circuits. In this subfield of mathematical and computational biology, ordinary differential equations (ODEs) are used to describe the transcriptional and translational processes over time, predict the behavior of the desired circuit and also to support their further development such as optimizing for a desired output if enough data is available (Chen et al., 1999).

Fig. 1:

Finding the CARTELTM AND gate

Finding the CARTELTM AND gate

The ODEs, that have been used to describe the different AND gate possibilities, consist of a set of parameters and a system of functions and their derivatives. How they can be set up in their simplest form is shown below.

f't=yz-k1*ft

(1)

z'(x)=k2*f(t)-k3*z(t)

(2)

The variables are functions of time t where f(t) describes the mRNA concentration, y(z) the transcription function and z(t) the protein concentration. Rate constants are enlisted in the following table.

Rate constant Description
k1 mRNA degradation rate
k2 Translation rate
k3 Protein degradation rate

This system of ODEs can now be solved via numerical integration, but to obtain constants like k1, k2, k3, experimental data has to be produced that is suitable for a nonlinear regression (Ingalls et al., 2012).

The obtained model is to be compared with new experimental data in order to verify the parameter sets. If necessary, parameters or assumptions have to be corrected.

Rate constant Description
k4 Basal expression rate
k5 Maximal expression rate
k6 Degradation rate