• Purpose of this Section

Now that we have obtained a genetic network corresponding to our project, we will analyse it through modeling. Therefore, you will find in this page the principal results coming from the models, as well as some resulting simulations.

FIFO behaviour

We have designed a model corresponding to the genetic network and we have obtained the following results :

The parameters found in the papers we have used directly lead to FIFO behaviour !

To go further into :

• the model ?
• the mathematical analysis and the simulations ?

Oscillations

Then, we have simulated the FIFO with a negative feedback, in order to observe oscillations. We have obtained the following results :



The first conclusion one can draw is that, with parameters found in the litterature ('biological parameters') the system reaches a steady state and is far from oscillating. Therefore, we have used the model to infer the modifications (that means the experiments to carry out) that had to be undertaken on the biological system to change its stability. Here are some of the theoretical results of the modifications :

Reducing EnvZ --> FlhDC

Reducing FliA --> FliA

Combining various modifications

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• the model ?
• the mathematical analysis and the simulations ?
• the changing of the parameters ?

System Improvements

Basically, we had to explore other possibilities to obtain oscillations. After just trying to tune the parameters, we have decided to add a supplementary delay in the system, in order to allow oscillations to appear. Thus we have decided to use Quorum sensing mechanisms that will bring both this needed delay and a synchronization among the population.

-*-*-*-*-*-*-*-*-> Ici une figure pour illustrer les oscillations du système complet <-*-*-*-*-*-*-*-*

All the details can be found here :

• System Improvements.

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