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Team:Montgomery Cougars NJUSA/Project/MathematicalModel
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In order to obtain optimal results from each one of our experiments, the Montgomery iGEM team has undertaken the challenge of using differential calculus concepts to model the rates of growth of protein. We seek to determine the amount of proteins expressed by the bacteria's gene. The quantity of protein yielded by the bacteria is especially important due to the exacting amount of protein necessary to effectively alter enough sebum molecules and cut off P. acnes's nutrient source. | In order to obtain optimal results from each one of our experiments, the Montgomery iGEM team has undertaken the challenge of using differential calculus concepts to model the rates of growth of protein. We seek to determine the amount of proteins expressed by the bacteria's gene. The quantity of protein yielded by the bacteria is especially important due to the exacting amount of protein necessary to effectively alter enough sebum molecules and cut off P. acnes's nutrient source. | ||
| + | ==Defining our Model== | ||
We are using the logistic growth equation to base our model on. <center>[[File:logisticgrowth.jpg|Logistic Growth]]</center> | We are using the logistic growth equation to base our model on. <center>[[File:logisticgrowth.jpg|Logistic Growth]]</center> | ||
{{Montgomery_Cougars_NJUSA/Layout_End:Two_Column}} | {{Montgomery_Cougars_NJUSA/Layout_End:Two_Column}} | ||
Revision as of 18:27, 16 June 2014
Mathematical Model
Purpose
In order to obtain optimal results from each one of our experiments, the Montgomery iGEM team has undertaken the challenge of using differential calculus concepts to model the rates of growth of protein. We seek to determine the amount of proteins expressed by the bacteria's gene. The quantity of protein yielded by the bacteria is especially important due to the exacting amount of protein necessary to effectively alter enough sebum molecules and cut off P. acnes's nutrient source.
Defining our Model
We are using the logistic growth equation to base our model on.
