Team:HZAU-China/Modeling/Gray logistic
From 2013.igem.org
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<p style="font-size:16px;font-family:arial, sans-serif;">The solution of the equation is :<a><img width="250" src="https://static.igem.org/mediawiki/2013/4/4c/2000000000.png"></a></p> | <p style="font-size:16px;font-family:arial, sans-serif;">The solution of the equation is :<a><img width="250" src="https://static.igem.org/mediawiki/2013/4/4c/2000000000.png"></a></p> | ||
- | <p style="font-size:16px;font-family:arial, sans-serif;"><a><img width="" src="https://static.igem.org/mediawiki/2013/a/aa/4321.png"></a>is the number of bacterial population.r is population growth rate.To make it convenient to calculate,we simplify the equation<a><img width=" | + | <p style="font-size:16px;font-family:arial, sans-serif;"><a><img width="" src="https://static.igem.org/mediawiki/2013/a/aa/4321.png"></a>is the number of bacterial population.r is population growth rate.To make it convenient to calculate,we simplify the equation<a><img width="250" src="https://static.igem.org/mediawiki/2013/6/68/3_%E5%89%AF%E6%9C%AC11.png"></a>;A,B and r are unknown parameters. is the logarithm of the CFU of Bacillus subtilis.</p> |
- | <p style="font-size:16px;font-family:arial, sans-serif;"> | + | |
+ | <h3>Using the gray system theory to determine the parameters:</h3> | ||
+ | <p style="font-size:16px;font-family:arial, sans-serif;">To determine the parameters of the equation,we use the gray system theory.The equation can be rewritten :<a><img width="250" src="https://static.igem.org/mediawiki/igem.org/0/09/4.png"></a>;</p> | ||
<p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | <p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | ||
<p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | <p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | ||
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<p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | <p style="font-size:16px;font-family:arial, sans-serif;">段落</p> | ||
Revision as of 12:57, 25 September 2013
Aim:
To know the growth curve in the dog’s blood
Steps:
1.Do experiment to measure the number of bacteria;
2.Establish the gray logistic model to simulate the growth of bacteria;
3.Determine the parameter through the experiment;
4.Test the predicted results.
Results:
The gray logistic model gets the good forecasting result.And the model precision is excellent.
Background:
The color of blood is so deep that it is not fit to measure the OD value to determine the growth of bacteria in the blood.Then we choose dilution-plate method to detect the number of total bacteria. So we coated a large number of plates.The logistic model of population can well predict the increase of population.
Establish the logistic model:
In the environment of the blood,the number of bacteria have a maximum value K.And when the number of bacteria approach K,the growth rate is next to nil.Then the population growth equation is as follows:
The solution of the equation is :
is the number of bacterial population.r is population growth rate.To make it convenient to calculate,we simplify the equation;A,B and r are unknown parameters. is the logarithm of the CFU of Bacillus subtilis.
Using the gray system theory to determine the parameters:
To determine the parameters of the equation,we use the gray system theory.The equation can be rewritten :;
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