Difference between revisions of "Team:Edinburgh OG/Model"
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<p>Therefore, main objective was to develop a mathematical model describing interactions between populations of lysogenic and lytic phages as well as bacteria in one system in continuous and batch processes. This was done by augmenting separate existing | <p>Therefore, main objective was to develop a mathematical model describing interactions between populations of lysogenic and lytic phages as well as bacteria in one system in continuous and batch processes. This was done by augmenting separate existing | ||
models of bacteria-phage interactions described as systems of ordinary (ODEs) and delayed differential equations (DDEs). The model was then used to:</p> | models of bacteria-phage interactions described as systems of ordinary (ODEs) and delayed differential equations (DDEs). The model was then used to:</p> | ||
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<li>Run simulations of a continuous process in Python using PyDDE package for solving systems of DDEs and compare the change in populations relative to the previous separate models of lytic phage and bacteria (Levin, Stewart and Chao, 1977), and lysogenic | <li>Run simulations of a continuous process in Python using PyDDE package for solving systems of DDEs and compare the change in populations relative to the previous separate models of lytic phage and bacteria (Levin, Stewart and Chao, 1977), and lysogenic | ||
phage and bacteria interactions in chemostat (Qiu, 2007).</li> | phage and bacteria interactions in chemostat (Qiu, 2007).</li> | ||
<li>Perform a local sensitivity analysis of the model parameters by calculating the elasticity for each parameter in Python to identify the key parameters that are largely responsible for the variation in the model output.</li> | <li>Perform a local sensitivity analysis of the model parameters by calculating the elasticity for each parameter in Python to identify the key parameters that are largely responsible for the variation in the model output.</li> | ||
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<a class="btn-ref" data-wow-delay=".9s" href="https://2017.igem.org/Team:Edinburgh_OG/Model:References" style="visibility: visible; animation-delay: 0.9s;">Full list of references</a> | <a class="btn-ref" data-wow-delay=".9s" href="https://2017.igem.org/Team:Edinburgh_OG/Model:References" style="visibility: visible; animation-delay: 0.9s;">Full list of references</a> | ||
Revision as of 23:59, 1 November 2017
Model: Methodology
Project goal and rationale
The overall goal of PhagED is to stop infections and deaths caused by antibiotic resistant pathogens. In the strategy that we use, the key step is to re-sensitise antibiotic resistant populations of bacteria using a system of two phages. In order to improve our understanding of complex interactions between these populations and at the same time to overcome the limitations imposed by the lack resources, such as finance and time available for the research, we developed an in silico model.
Therefore, main objective was to develop a mathematical model describing interactions between populations of lysogenic and lytic phages as well as bacteria in one system in continuous and batch processes. This was done by augmenting separate existing models of bacteria-phage interactions described as systems of ordinary (ODEs) and delayed differential equations (DDEs). The model was then used to:
- Run simulations of a continuous process in Python using PyDDE package for solving systems of DDEs and compare the change in populations relative to the previous separate models of lytic phage and bacteria (Levin, Stewart and Chao, 1977), and lysogenic phage and bacteria interactions in chemostat (Qiu, 2007).
- Perform a local sensitivity analysis of the model parameters by calculating the elasticity for each parameter in Python to identify the key parameters that are largely responsible for the variation in the model output.
Background
Here we review existing models of bacteria-phage interactions considering assumptions and limitations of each model.
Methodology
Here we present the methodology that were used for the model.
Results
Here we present the results of simulations of newly created models, review and analyse together with comparison to other models.
References
We gathered almost all up-to-date scientific literature about phage-bacteria interactions.
Full list of references
