Difference between revisions of "Team:Manchester/Model"

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<p>We used modelling in three ways to inform different parts of the project:</p>
 
<p style="margin-left: 40px">1. The statistical Design of Experiments (DoE) was used to design the most efficient experiments to determine the factors influencing the activity of our key enzyme. Two rounds of DoE enabled us to identify the optimal conditions for testing of our experimental system</p>
 
<p style="margin-left: 40px">1. The statistical Design of Experiments (DoE) was used to design the most efficient experiments to determine the factors influencing the activity of our key enzyme. Two rounds of DoE enabled us to identify the optimal conditions for testing of our experimental system</p>
 
<p style="margin-left: 40px">2. Continuous culture modelling was used to predict the rate at which Phosphostore devices could be produced on different substrates. This allowed us to estimate the yearly cost of treating wastewater using phosphostore. As a result we performed a major re-design of the intended Phosphostore device, assessing the cost reduction potential of different growth conditions and experimental strategies by computational modelling</p>
 
<p style="margin-left: 40px">2. Continuous culture modelling was used to predict the rate at which Phosphostore devices could be produced on different substrates. This allowed us to estimate the yearly cost of treating wastewater using phosphostore. As a result we performed a major re-design of the intended Phosphostore device, assessing the cost reduction potential of different growth conditions and experimental strategies by computational modelling</p>

Revision as of 18:29, 31 October 2017

Modelling


We used modelling in three ways to inform different parts of the project:

1. The statistical Design of Experiments (DoE) was used to design the most efficient experiments to determine the factors influencing the activity of our key enzyme. Two rounds of DoE enabled us to identify the optimal conditions for testing of our experimental system

2. Continuous culture modelling was used to predict the rate at which Phosphostore devices could be produced on different substrates. This allowed us to estimate the yearly cost of treating wastewater using phosphostore. As a result we performed a major re-design of the intended Phosphostore device, assessing the cost reduction potential of different growth conditions and experimental strategies by computational modelling

3. An innovative ensemble modelling approach was used to predict the behaviour of our recombinant phosphate starvation operon in addition to native PHO regulon as a regulatory system for controlling microcompartment synthesis. This helped us to choose the appropriate regulatory parts for our experimental design


Design of Experiments


Continuous Culture


Phosphate Starvation Operon