# Alondra Vega: Week 4

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## Terminology

- The
**Michaelis-Menten**equation describes the relationship between the rate of a substrate conversion by an enzyme to the concentration of the substrate in the equation. V is the rate of conversion, [S] is the substrate concentration and K_{m}is the Michaelis constant. K_{m}approximates the affinity of enzyme for the substrate. - The
**Lineweaver-Burk**experiment shows a way of illustrating kinetic date. The plot is produced by taking the reciprocal of the Michaelis-Menten equation. It will usually produce a linear function y = mx + b. - A
**chemostat reaction**deals with the flow rate into the system and the flow rate out of the system. A mathematical model is used (a set of differential equations) to see the change in the steady state, or to find what the steady state is. **Exponential growth**(including exponential decay) occurs when the growth rate of a mathematical function is proportional to the function's current value. It will produce a similar curve to e^{x}when plotted.

## Applying Michaelis-Menten Model

- In was not sure what was being asked when working with this code. I was not sure what program I was supposed to use. I used the michaelis_menten, catalysis and catalysis-driver. I am not sure what the differences are between catalysis and the Lineweaver-Burke program, so I stayed with the program that we worked on last week, since i do not feel that we went into depth the other program. I also do not know what the graphs are saying. I feel that I would have been able to compare them better if they were not all in the same plot. I would have been able to see which belong to which k
_{-1}value. I know that there are settings to differentiate between the graphs, but I have not mastered those skills yet. The graphs provided below show the graphs that the catalysis driver produces. - When k
_{-1}=0.

- When k
_{-1}=1.

- When k
_{-1}=5.

## Estimating Michaelis-Menten Parameters

- After working on excel with the Lineweaver-Burke technique with the given points, I found that V
_{max}was 0.031551 and K was 27.10932. Vmax is found was by taking the inverse of the y-intercept on the trendline that we added on the graph. the K value was found by taking the slope of the line and dividing it by the intercept.