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− | <h1 style="font-size: 4vw; font-family:Montserrat;"class="w100" ><b> | + | <h1 style="font-size: 4vw; font-family:Montserrat;"class="w100" ><b>MODELLING</b></h1> |
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− | + | The evolution of our bacteria-phage dynamic model helped us gain a better understanding of the interaction between a bacteria population and a phage population and its impact on the viability of our design. After defining a variety of parameters and making several assumptions, we showed that it is possible for our system of bacteria and phages to be self-sustainable. Comparing our model with our experimental results, we developed a second model where we accounted for additional factors such as a possible mutation in the bacteria’s DNA that results in resistance against phage infection. Furthermore, we modelled the copper-binding efficiency of CUP I (our copper-binding protein) to estimate the optimal ratio of enzyme and copper concentrations that would result in the most efficient binding in the implementation of our system. | |
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+ | <h2>Discrete Time Model</h2> | ||
+ | <p style="font-size: 18px; font-family: 'Open Sans'"><b>Purpose:</b>Given an initial Multiplicity of Infection (MOI) and infection onset point (during a bacteria lifecycle), determine how the populations of bacteria and phages change over discrete time intervals.</p> | ||
+ | <p style="font-size: 18px; font-family: 'Open Sans'"><b>Assumptions</b> | ||
<p><h1></h1> <b></b> | <p><h1></h1> <b></b> | ||
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Revision as of 04:38, 17 October 2018
MODELLING
The evolution of our bacteria-phage dynamic model helped us gain a better understanding of the interaction between a bacteria population and a phage population and its impact on the viability of our design. After defining a variety of parameters and making several assumptions, we showed that it is possible for our system of bacteria and phages to be self-sustainable. Comparing our model with our experimental results, we developed a second model where we accounted for additional factors such as a possible mutation in the bacteria’s DNA that results in resistance against phage infection. Furthermore, we modelled the copper-binding efficiency of CUP I (our copper-binding protein) to estimate the optimal ratio of enzyme and copper concentrations that would result in the most efficient binding in the implementation of our system.
Discrete Time Model
Purpose:Given an initial Multiplicity of Infection (MOI) and infection onset point (during a bacteria lifecycle), determine how the populations of bacteria and phages change over discrete time intervals.
Assumptions