HEARTBEAT Fuzzy Modeling

Results

Modeling inducible promoters

Based on prior data analysis of data derived from flow cytometry experiments using inducible synthetic NFkB responsive promoters we developed a fuzzy controller which reflects the behavior of inducible promoters.

By using our model we were able to capture the basic behaviour of an inducible promoter (Fig.1).

Figure 1:

Once this was accomplished, we aimed for capturing the dependency of the activity of the promoter on more heterogeneous parameters, such as affinity score, position score and presence stimulation (Figs. 2a and 2b)

Figure 2a:

Figure 2b:

Figure 3:

Our final model of an inducible promoters (Figure: NFkB 1) shows the relationship between stimuli, type of promoter, i.e. inducible, affinity score and position score. The model predicted a high dependency of the promoter activity on affinity score revealing its crucial role (in TF binding). dazu: "position score gives the last small jump" to the promoter to be an optimal promoter.

what is the model good for: importantly, our model captures the behaviour of an inducible promoter. we next wondered wheter we would be able to establish the same for an non-inducible promoter

from here: constitutives

later on: we have ... for the inducibles, ... for the constitutives. now: could this be fused(?) for a prediction of combinatorial behaviour of

point out: different promoter design, different experimental measuerment, as well as literature data -> final model?

and then jump to final model.