Team:Manchester/Model/MechanismUncertainty
Network Mechanism Analysis
Contents
Overview and Motivation Methodology Results ConclusionsOverview and Motivation
During discussions with the experimental team it became clear to us that the exact reaction mechanism in place was not clearly understood. By modelling a range of different potential mechanisms and comparing the outputs to experimental data we could draw conclusions about the accuracy of the mechanisms and hence refine the model in an effort to produce more accurate predictions and improve our understanding of the system.
There were a few different mechanisms tested in this analysis
| Step One | Step Two |
|---|---|
| Irreversible Michaelis-Menten Kinetics | Irreversible Michaelis-Menten Kinetics |
| Reversible Michaelis-Menten Kinetics | Reversible Michaelis-Menten Kinetics |
| Uni-Bi Kinetics | Bi-Uni Kinetics |
Methodology
For each of the combinations of potential rate equations for each step the following was undertaken:
The model was run with many iterations. The concentration at steady state for each iteration was recorded and plotted in a histogram. Experimental steady state data was then compared to these histograms.
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PLACEHOLDER FOR GRAPHS, 2D and 3D
Return to top of pageConclusions
From the graphs you can clearly see that the minimum cost can be achieved with the range GOx fraction = XXX-YYY, however it is also shown that at additional cost expense, the time to expression can be reduced if required. The ranges identified as of interest should be tested experimentally to further validate these results. In some situations the constraints are not met for example at a GOx fraction of 0 or 1 in all situations, but also some ranges between these dependant on the constraint set. The points of constraint failure could also be experimentally validated.
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