Difference between revisions of "Team:FAFU-CHINA/Modeling"

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<div id="div1"><img src="https://static.igem.org/mediawiki/2015/3/36/Fafu_5.JPG"/></div>
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<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>In FAFU’s project, it is difficult to measure the quantitative data and determine the amount of dsRNAs which is fed to the larvae. So in the modeling part, we devoted to establishing an accurate mathematical model to simulate the dsRNA expression according to the mechanism of T7 promoter. After the model is built, we can determine the relationship between the concentration of IPTG and the production of dsRNA . Then we can control  the amount of dsRNAs which if fed to the larvae by controlling the concentration of IPTG easily.</p></div><br>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
  
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<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>We know that T7 promoter is a kind of inducible promoter. Hill equation can be used to simulate the effect of T7 promoter. In T7 strength model, the independent variable is the concentration of IPTG, and the dependent variable is the production of dsRNA.</p></div>
+
display:inline-block; width:25px;"></span>In FAFU’s project, it
 +
 
 +
is difficult to measure the quantitative data and determine the
 +
 
 +
amount of dsRNAs which is fed to the larvae. So in the modeling
 +
 
 +
part, we devoted to establishing an accurate mathematical model to
 +
 
 +
simulate the dsRNA expression according to the mechanism of T7
 +
 
 +
promoter. After the model is built, we can determine the
 +
 
 +
relationship between the concentration of IPTG and the production
 +
 
 +
of dsRNA . Then we can control  the amount of dsRNAs which if fed
 +
 
 +
to the larvae by controlling the concentration of IPTG
 +
 
 +
easily.</p></div><br>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;  
 +
 
 +
display:inline-block; width:25px;"></span>We know that T7 promoter  
 +
 
 +
is a kind of inducible promoter. Hill equation can be used to  
 +
 
 +
simulate the effect of T7 promoter. In T7 strength model, the  
 +
 
 +
independent variable is the concentration of IPTG, and the  
 +
 
 +
dependent variable is the production of dsRNA.</p></div>
  
 
<br>
 
<br>
−
<div id="sub"><div id="headline2">1.The Model Simulating the Change of dsRNA with Time in Different Concentration of IPTG</div></div>
+
<div id="sub"><div id="headline2">1.The Model Simulating the  
 +
 
 +
Change of dsRNA with Time in Different Concentration of  
 +
 
 +
IPTG</div></div>
 
<br>
 
<br>
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>By observing the pattern of the data, we figure out that the Logistic equation, which is often used to simulate the growth of population, can model the trend best. Thus, we adapt the formula<img src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png" height="53" width="178" />in the following fitting, where a is the concentration of dsRNA in the steady state.</p></div><br>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
  
−
<div id="sub"><p>When the concentration of IPTG=0.3mmol/L, the result of curve fitting is: </p></div>
+
display:inline-block; width:25px;"></span>By observing the pattern
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>General model: <img src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png" height="53" width="178" /></p></div>
+
of the data, we figure out that the Logistic equation, which is
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Coefficients (with 95% confidence bounds): </p></div>
+
often used to simulate the growth of population, can model the
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>a = 0.3241 (0.299, 0.3492)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>b = 35.95 (-79.99, 151.9)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>c = 1.829 (0.3231, 3.334)</p></div>
+
  
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<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Goodness of fit: </p></div>
+
trend best. Thus, we adapt the formula<img
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>SSE: 0.00333</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>R-square: 0.9676</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>Adjusted R-square: 0.9567</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>RMSE: 0.02356</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/2/2c/FAFU-CHINA_MD2.png" height="393.3" width="608.4"/></p></div>
+
src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png"  
  
−
<div id="sub"><i><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 1: The curve is matched by the formula mentioned above.</i></div>
+
height="53" width="178" />in the following fitting, where a is the  
  
−
<div id="sub"><p>When the concentration of IPTG=0.4mmol/L, the result of curve fitting is: </p></div>
+
concentration of dsRNA in the steady state.</p></div><br>
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>General model: <img src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png" height="53" width="178" /></p></div>
+
<div id="sub"><p>When the concentration of IPTG=0.3mmol/L, the
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Coefficients (with 95% confidence bounds): </p></div>
+
result of curve fitting is: </p></div>
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>a = 0.3474 (0.3261, 0.3686)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>b = 46.66 (-63.55, 156.9)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>c = 1.828 (0.7647, 2.892)</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Goodness of fit: </p></div>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>SSE: 0.00232</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>R-square: 0.9808</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>Adjusted R-square: 0.9744</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>RMSE: 0.01966</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/e/ea/FAFU-CHINA_MD3.png" height="393.3" width="608.4"/></p></div>
+
display:inline-block; width:25px;"></span>General model: <img  
  
−
<div id="sub"><i><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 2: The curve is matched by the formula mentioned above.</i></div>
+
src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png"
  
−
<div id="sub"><p>When the concentration of IPTG=0.5mmol/L, the result of curve fitting is: </p></div>
+
height="53" width="178" /></p></div>
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>General model: <img src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png" height="53" width="178" /></p></div>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Coefficients (with 95% confidence bounds): </p></div>
+
display:inline-block; width:25px;"></span>Coefficients (with 95%  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>a = 0.3465 (0.3206, 0.3723)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>b = 49.63 (-79.79, 179)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>c = 1.76 (0.6333, 2.886)</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Goodness of fit: </p></div>
+
confidence bounds): </p></div>
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>SSE: 0.003338</p></div>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>R-square: 0.9732</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>Adjusted R-square: 0.9642</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>RMSE: 0.02359</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/e/e6/FAFU-CHINA_MD4.png" height="393.3" width="608.4"/></p></div>
+
display:inline-block; width:50px;"></span>a = 0.3241 (0.299,
  
−
<div id="sub"><i><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 3: The curve is matched by the formula mentioned above.</i></div>
+
0.3492)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>b = 35.95 (-79.99,
 +
 
 +
151.9)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>c = 1.829 (0.3231,
 +
 
 +
3.334)</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Goodness of fit:
 +
 
 +
</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>SSE: 0.00333</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>R-square:
 +
 
 +
0.9676</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>Adjusted R-square:
 +
 
 +
0.9567</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>RMSE: 0.02356</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/2/2c/FAFU-CHINA_MD2.png"
 +
 
 +
height="393.3" width="608.4"/></p></div>
 +
 
 +
<div id="sub"><i><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Figure 1: The curve is
 +
 
 +
matched by the formula mentioned above.</i></div>
 +
 
 +
<div id="sub"><p>When the concentration of IPTG=0.4mmol/L, the
 +
 
 +
result of curve fitting is: </p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>General model: <img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png"
 +
 
 +
height="53" width="178" /></p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Coefficients (with 95%
 +
 
 +
confidence bounds): </p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>a = 0.3474 (0.3261,
 +
 
 +
0.3686)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>b = 46.66 (-63.55,
 +
 
 +
156.9)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>c = 1.828 (0.7647,
 +
 
 +
2.892)</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Goodness of fit:
 +
 
 +
</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>SSE: 0.00232</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>R-square:
 +
 
 +
0.9808</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>Adjusted R-square:
 +
 
 +
0.9744</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>RMSE: 0.01966</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/e/ea/FAFU-CHINA_MD3.png"
 +
 
 +
height="393.3" width="608.4"/></p></div>
 +
 
 +
<div id="sub"><i><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Figure 2: The curve is
 +
 
 +
matched by the formula mentioned above.</i></div>
 +
 
 +
<div id="sub"><p>When the concentration of IPTG=0.5mmol/L, the
 +
 
 +
result of curve fitting is: </p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>General model: <img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/6/67/FAFU-CHINA_MD1.png"
 +
 
 +
height="53" width="178" /></p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Coefficients (with 95%
 +
 
 +
confidence bounds): </p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>a = 0.3465 (0.3206,
 +
 
 +
0.3723)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>b = 49.63 (-79.79, 179)
 +
 
 +
</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>c = 1.76 (0.6333,
 +
 
 +
2.886)</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Goodness of fit:
 +
 
 +
</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>SSE: 0.003338</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>R-square:
 +
 
 +
0.9732</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>Adjusted R-square:
 +
 
 +
0.9642</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>RMSE: 0.02359</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/e/e6/FAFU-CHINA_MD4.png"
 +
 
 +
height="393.3" width="608.4"/></p></div>
 +
 
 +
<div id="sub"><i><span style="display:-moz-inline-box;  
 +
 
 +
display:inline-block; width:25px;"></span>Figure 3: The curve is  
 +
 
 +
matched by the formula mentioned above.</i></div>
  
 
<br>
 
<br>
Line 163: Line 362:
 
<br>
 
<br>
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>By the work of first part, it is found that the concentration of dsRNA will become steady after around 4 hours, so we regard the concentration of dsRNA after 4 hours’ culture as that of steady state. Then the Hill equation is applied to model the relationship between the concentration of IPTG and the production of dsRNA, the result of curve fitting is: (where  is the maximal data we can get from the data)</p></div><br>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>General model: <img src="https://static.igem.org/mediawiki/2015/f/f2/FAFU-CHINA_MD5.png" height="53" width="178" /></p></div>
+
display:inline-block; width:25px;"></span>By the work of first
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Coefficients (with 95% confidence bounds): </p></div>
+
part, it is found that the concentration of dsRNA will become
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>Xm = 0.1265 (0.08411, 0.1689)</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>n = 2.239 (0.8187, 3.658)</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Goodness of fit: </p></div>
+
steady after around 4 hours, so we regard the concentration of  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>SSE: 0.003107</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>R-square: 0.9062</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>Adjusted R-square: 0.8828</p></div>
+
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:50px;"></span>RMSE: 0.02787</p></div>
+
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/7/73/FAFU-CHINA_MD6.png" height="393.3" width="608.4"/></p></div>
+
dsRNA after 4 hours’ culture as that of steady state. Then the
  
−
<div id="sub"><i><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 4: The curve is matched by the formula mentioned above.</i></div>
+
Hill equation is applied to model the relationship between the  
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>We sorted out data and parameters and then beautified the graph.</p></div>
+
concentration of IPTG and the production of dsRNA, the result of
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/d/d6/FAFU-CHINA_MD7.png" width="608"/></p></div>
+
curve fitting is: (where  is the maximal data we can get from the
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span><img src="https://static.igem.org/mediawiki/2015/e/ea/FAFU-CHINA_MD8.png" height="393.3" width="608.4"/></p></div>
+
data)</p></div><br>
  
−
<div id="sub"><i><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 5: It shows the relationship between the concentration of IPTG and the production of dsRNA.</i></div>
+
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>General model: <img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/f/f2/FAFU-CHINA_MD5.png"
 +
 
 +
height="53" width="178" /></p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Coefficients (with 95%
 +
 
 +
confidence bounds): </p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>Xm = 0.1265 (0.08411,
 +
 
 +
0.1689)</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>n = 2.239 (0.8187,
 +
 
 +
3.658)</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Goodness of fit:
 +
 
 +
</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>SSE: 0.003107</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>R-square:
 +
 
 +
0.9062</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>Adjusted R-square:
 +
 
 +
0.8828</p></div>
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:50px;"></span>RMSE: 0.02787</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/7/73/FAFU-CHINA_MD6.png"
 +
 
 +
height="393.3" width="608.4"/></p></div>
 +
 
 +
<div id="sub"><i><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>Figure 4: The curve is
 +
 
 +
matched by the formula mentioned above.</i></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span>We sorted out data and
 +
 
 +
parameters and then beautified the graph.</p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/d/d6/FAFU-CHINA_MD7.png"
 +
 
 +
width="608"/></p></div>
 +
 
 +
<div id="sub"><p><span style="display:-moz-inline-box;
 +
 
 +
display:inline-block; width:25px;"></span><img
 +
 
 +
src="https://static.igem.org/mediawiki/2015/e/ea/FAFU-CHINA_MD8.png"
 +
 
 +
height="393.3" width="608.4"/></p></div>
 +
 
 +
<div id="sub"><i><span style="display:-moz-inline-box;  
 +
 
 +
display:inline-block; width:25px;"></span>Figure 5: It shows the  
 +
 
 +
relationship between the concentration of IPTG and the production  
 +
 
 +
of dsRNA.</i></div>
  
 
<br>
 
<br>
  
−
<div id="sub"><p><span style="display:-moz-inline-box; display:inline-block; width:25px;"></span>Figure 5 shows the relationship between the concentration of IPTG and the production of dsRNA. According to this mathematical model, we can work out the accurate production of dsRNA which is fed to the larvae with the concentration of IPTG which is put into the bacterial system to induce T7 promoter.</p></div>
+
<div id="sub"><p><span style="display:-moz-inline-box;  
 +
 
 +
display:inline-block; width:25px;"></span>Figure 5 shows the  
 +
 
 +
relationship between the concentration of IPTG and the production  
 +
 
 +
of dsRNA. According to this mathematical model, we can work out  
 +
 
 +
the accurate production of dsRNA which is fed to the larvae with  
 +
 
 +
the concentration of IPTG which is put into the bacterial system  
 +
 
 +
to induce T7 promoter.</p></div>
  
 
<br>
 
<br>

Revision as of 21:55, 18 September 2015

Modeling





Modeling


In FAFU’s project, it is difficult to measure the quantitative data and determine the amount of dsRNAs which is fed to the larvae. So in the modeling part, we devoted to establishing an accurate mathematical model to simulate the dsRNA expression according to the mechanism of T7 promoter. After the model is built, we can determine the relationship between the concentration of IPTG and the production of dsRNA . Then we can control the amount of dsRNAs which if fed to the larvae by controlling the concentration of IPTG easily.


We know that T7 promoter is a kind of inducible promoter. Hill equation can be used to simulate the effect of T7 promoter. In T7 strength model, the independent variable is the concentration of IPTG, and the dependent variable is the production of dsRNA.


1.The Model Simulating the Change of dsRNA with Time in Different Concentration of IPTG

By observing the pattern of the data, we figure out that the Logistic equation, which is often used to simulate the growth of population, can model the trend best. Thus, we adapt the formulain the following fitting, where a is the concentration of dsRNA in the steady state.


When the concentration of IPTG=0.3mmol/L, the result of curve fitting is:

General model:

Coefficients (with 95% confidence bounds):

a = 0.3241 (0.299, 0.3492)

b = 35.95 (-79.99, 151.9)

c = 1.829 (0.3231, 3.334)

Goodness of fit:

SSE: 0.00333

R-square: 0.9676

Adjusted R-square: 0.9567

RMSE: 0.02356

Figure 1: The curve is matched by the formula mentioned above.

When the concentration of IPTG=0.4mmol/L, the result of curve fitting is:

General model:

Coefficients (with 95% confidence bounds):

a = 0.3474 (0.3261, 0.3686)

b = 46.66 (-63.55, 156.9)

c = 1.828 (0.7647, 2.892)

Goodness of fit:

SSE: 0.00232

R-square: 0.9808

Adjusted R-square: 0.9744

RMSE: 0.01966

Figure 2: The curve is matched by the formula mentioned above.

When the concentration of IPTG=0.5mmol/L, the result of curve fitting is:

General model:

Coefficients (with 95% confidence bounds):

a = 0.3465 (0.3206, 0.3723)

b = 49.63 (-79.79, 179)

c = 1.76 (0.6333, 2.886)

Goodness of fit:

SSE: 0.003338

R-square: 0.9732

Adjusted R-square: 0.9642

RMSE: 0.02359

Figure 3: The curve is matched by the formula mentioned above.

2.The Hill Equation

By the work of first part, it is found that the concentration of dsRNA will become steady after around 4 hours, so we regard the concentration of dsRNA after 4 hours’ culture as that of steady state. Then the Hill equation is applied to model the relationship between the concentration of IPTG and the production of dsRNA, the result of curve fitting is: (where is the maximal data we can get from the data)


General model:

Coefficients (with 95% confidence bounds):

Xm = 0.1265 (0.08411, 0.1689)

n = 2.239 (0.8187, 3.658)

Goodness of fit:

SSE: 0.003107

R-square: 0.9062

Adjusted R-square: 0.8828

RMSE: 0.02787

Figure 4: The curve is matched by the formula mentioned above.

We sorted out data and parameters and then beautified the graph.

Figure 5: It shows the relationship between the concentration of IPTG and the production of dsRNA.

Figure 5 shows the relationship between the concentration of IPTG and the production of dsRNA. According to this mathematical model, we can work out the accurate production of dsRNA which is fed to the larvae with the concentration of IPTG which is put into the bacterial system to induce T7 promoter.