Modelling Notebook

Week 1 08/06/09 - 12/06/09

We split into pairs and began writing a system of ODEs for each of our three possible wiring diagrams. The aim of this was to decide which genetic circuitry would work best, depending on how the models performed. In order to get any data out the models however we had to ask the biologists on the team to help us find parameters, although this proved to be challenging.
Started to program our ODE's into our RK4 program (written in C)

It became apparent, from the modeling, that the third circuit design was superiour to the other two for several reasons. As such the biologists could start thinking about starting their lab work.
Monte Carlo simulations were written in C to test the viability and robustness of our model

First proper chemotaxis model’s created without animation, and could only handle a few bacteria at a time Consideration went into more practical sides of the chemotaxis, such as average time to travel a distance. Bacteria respond to a concentration, as opposed to distance. This was done in Matlab.
ODEs were refined and internal dynamics of the cell were studied further.
PDEs were investigated as a possible way to integrate several components of models

Program written to estimate the point at which quorum sensing would turn on by simplifying system to steady state bacteria each producing HSL in a control volume of water.
Equations were added to the ODEs to describe the transcription of mRNA molecules.
PDEs turned out be too difficult to model, as a result the chemotaxis model was converted into C so that it would be possible to merge both the chemotaxis and internal dynamics into a single working model.

The program simulating quorum sensing level is incorporated into a population model so that population grows, and with this HSL, until lysis occurs and population decreases. Time for lysis must be less than the replicating time or else the population will not die. (although growth may stop when quorum sensing turns on, as protein production will inhibit growth).
ODEs were revised after input from the biologists

SimBiology is first played with, but was difficult to customise to our needs and so work was continued with the chemotaxis model in Matlab.
ODEs were revised again after consultation with the biologists.

A stochastic simulation was done of the deterministic model, using the tau-leap method. This was programed in C.
Further work was done on combining chemotaxis and internal dynamics in C.