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Team:British Columbia/Modeling
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Where $E(X_i)$ is the statistically expected infected bacterial populations. We define the rate of change in population in () and (). | Where $E(X_i)$ is the statistically expected infected bacterial populations. We define the rate of change in population in () and (). | ||
\begin{align} | \begin{align} | ||
| - | \frac{dX_u}{dt} = \mu_u + | + | &\frac{dX_u}{dt} = \big(\mu_u + k_{d_u}\big)X_u\\ |
| + | &\frac{dX_i}{dt} = \big(\mu_i + k_{d_i}\big)X_i | ||
| + | \end{align} | ||
| + | To create a more complete model, we have chosen to model the bacteriophage population as well. | ||
| + | \begin{align} | ||
| + | P = X_i \beta ^{\frac{\tau}{LT}} | ||
| + | \end{align} | ||
| + | However, due to the low rate of secretion of our studied populations, we can redefine our phage population as a stepwise function: | ||
| + | \begin{align} | ||
| + | \frac{dP}{dt} = E(X_i)\beta, &for lysis | ||
| + | \end{align} | ||
| + | |||
| + | The multiplicity of infection (MOI) is defined as the ratio of bacteriophages to bacterial cells. | ||
| + | \begin{align} | ||
| + | MOI = \frac{P}{X} | ||
\end{align} | \end{align} | ||
Revision as of 21:23, 31 August 2013
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Reaction Kinetics: - Modelling the production of cinnamaldehyde, vanillin and caffeine production
Population dynamics: - Modelling the population of a bacteria in a batch reactor with phage dependency
\begin{align} \frac{dX}{dt} = \frac{dX_u}{dt} + \frac{dX_i}{dt} + \Gamma \end{align} Where $\frac{dX}{dt}$ is rate of change in bacteria population over time, $\frac{dX_u}{dt}$ and $\frac{dX_i}{dt}$ are the rates of change in the uninfected and infected populations respectively. $\Gamma$ is defined as a stepwise function. \begin{align} \Gamma &= - E(X_i), \ during \ phage \ caused \ lysis\\ &= 0, \ \ \ \ \ \ \ \ \ \ \ \ \ \ otherwise \end{align} Where $E(X_i)$ is the statistically expected infected bacterial populations. We define the rate of change in population in () and (). \begin{align} &\frac{dX_u}{dt} = \big(\mu_u + k_{d_u}\big)X_u\\ &\frac{dX_i}{dt} = \big(\mu_i + k_{d_i}\big)X_i \end{align} To create a more complete model, we have chosen to model the bacteriophage population as well. \begin{align} P = X_i \beta ^{\frac{\tau}{LT}} \end{align} However, due to the low rate of secretion of our studied populations, we can redefine our phage population as a stepwise function: \begin{align} \frac{dP}{dt} = E(X_i)\beta, &for lysis \end{align}
The multiplicity of infection (MOI) is defined as the ratio of bacteriophages to bacterial cells. \begin{align} MOI = \frac{P}{X} \end{align}
