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Team:Oxford/modelling biosensor
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System Characterisation
Predicting the mCherry fluorescence
To model the first double repression, we took the fact that we won’t need to know the amount of tetR in the system and used the assumption that ATC is effectively activating the expression of dcmR, albeit parameterised by different constants. This assumption should be justified by the fact that we will be able to precisely control the addition of ATC and we will be able to measure the fluorescence of the mCherry.
We modelled this first step using both deterministic and stochastic models.
To model the first double repression, we took the fact that we won’t need to know the amount of tetR in the system and used the assumption that ATC is effectively activating the expression of dcmR, albeit parameterised by different constants. This assumption should be justified by the fact that we will be able to precisely control the addition of ATC and we will be able to measure the fluorescence of the mCherry.
We modelled this first step using both deterministic and stochastic models.
Predicting the mCherry fluorescence
To model the first double repression, we took the fact that we won’t need to know the amount of tetR in the system and used the assumption that ATC is effectively activating the expression of dcmR, albeit parameterised by different constants. This assumption should be justified by the fact that we will be able to precisely control the addition of ATC and we will be able to measure the fluorescence of the mCherry.
We modelled this first step using both deterministic and stochastic models.
To model the first double repression, we took the fact that we won’t need to know the amount of tetR in the system and used the assumption that ATC is effectively activating the expression of dcmR, albeit parameterised by different constants. This assumption should be justified by the fact that we will be able to precisely control the addition of ATC and we will be able to measure the fluorescence of the mCherry.
We modelled this first step using both deterministic and stochastic models.
