Team:KAIST Korea/Project Modeling

From 2012.igem.org

(Difference between revisions)
Line 152: Line 152:
<div>
<div>
<span id ="sub-sub-title">1] Cell Growth Curve</span></br></br>
<span id ="sub-sub-title">1] Cell Growth Curve</span></br></br>
-
<span id="little">Cell growth can be modeled using Logistic differential equation. The logistic equation is shown below.</span></br></br>
+
<span id="little">Cell growth can be modeled using Logistic differential equation, which is shown below.</span></br></br>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/a/a2/KAIST_Logistic_equation.png'/></div>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/a/a2/KAIST_Logistic_equation.png'/></div>
</br>
</br>
-
<span id="little">When we solve above equation with appropriate parameters(using MATLAB), we can get solution curve like below. This curve matches with our knowledge about cell growth.</span></br></br>
+
<span id="little">When we solve this equation with appropriate parameters(using MATLAB), we can get solution curve as shown below. This curve matches with our knowledge about cell growth.</span></br></br>
<div align="center" ><img src='#'/></div>
<div align="center" ><img src='#'/></div>
</br>
</br>
Line 168: Line 168:
<div>
<div>
<span id="sub-sub-title">2] Title???</span></br></br>
<span id="sub-sub-title">2] Title???</span></br></br>
-
<span id="little">With GFP and RFP, we want to check whether our system really works or not. Since we cannot consider all of complicated biological phenomena, we assume our system simply follows reaction rate theory and mass balance equations. Below reactions are simplified version of our system, and we CONSIDER the production and degradation of mRNAs and Genes, but we IGNORE the polysome phenomena and any gene regulatory system that is occur in real biological system. Also, we CONSIDER that there is many copies of plasmids in <i>E.coli</i> and each plasmid can react with invertase to invert their gene sequence.</br>
+
<span id="little">With GFP and RFP, we want to check whether our system really works or not. Since we cannot consider all the complicated biological phenomena, we assume our system simply follows reaction rate theory and mass balance equations. Reactions below are simplified version of our system. We CONSIDERED the production and degradation of mRNAs and Genes, while we IGNORED the polysome phenomena and any gene regulatory system that occurs in real biological system. Also, we CONSIDERED that there are many copies of plasmids in <i>E.coli</i> and each plasmid can react with invertase to invert their gene sequence.</br>
-
Because every plasmid have equal probability that react with invertase, we assume plasmids follow uniform distribution. Also assume each plasmids are mutually independent, that is each  plasmid cannot affect invertase reaction of other plasmid.</br></br>
+
Because every plasmid have equal probability to react with invertase, we assume plasmids follow uniform distribution. Final assumption is that each plasmids are mutually independent, that is, each  plasmid cannot affect invertase reaction of other plasmid.</br></br>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/d/d7/KAIST_Gfprfp.png'/></div>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/d/d7/KAIST_Gfprfp.png'/></div>
</br>
</br>
-
<span id='little'>Using these reaction, we construct mathematical model of our system that is shown below. Pg(gene probability), in our model, represents the number of plasmid which is inverted. And the rate of producing inverted gene is reduced as the remaining non-inverted gene is reduced.</span></br></br>
+
<span id='little'>Using these reaction, we constructed mathematical model of our system as shown below. Pg(gene probability), in our model, represents the number of plasmid which is inverted. And the rate of producing inverted gene is reduced as the remaining non-inverted gene is reduced.</span></br></br>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/b/b0/KAIST_Gfprfp2.png'/></div></br>
<div align="center" ><img src='https://static.igem.org/mediawiki/2012/b/b0/KAIST_Gfprfp2.png'/></div></br>

Revision as of 14:57, 26 October 2012

KAIST Korea 2012 iGEM

Project : Modeling
1] Cell Growth Curve 2] title?? 3] title??

Modeling

Computational modeling of our project

1] Cell Growth Curve

Cell growth can be modeled using Logistic differential equation, which is shown below.


When we solve this equation with appropriate parameters(using MATLAB), we can get solution curve as shown below. This curve matches with our knowledge about cell growth.






2] Title???

With GFP and RFP, we want to check whether our system really works or not. Since we cannot consider all the complicated biological phenomena, we assume our system simply follows reaction rate theory and mass balance equations. Reactions below are simplified version of our system. We CONSIDERED the production and degradation of mRNAs and Genes, while we IGNORED the polysome phenomena and any gene regulatory system that occurs in real biological system. Also, we CONSIDERED that there are many copies of plasmids in E.coli and each plasmid can react with invertase to invert their gene sequence.
Because every plasmid have equal probability to react with invertase, we assume plasmids follow uniform distribution. Final assumption is that each plasmids are mutually independent, that is, each plasmid cannot affect invertase reaction of other plasmid.


Using these reaction, we constructed mathematical model of our system as shown below. Pg(gene probability), in our model, represents the number of plasmid which is inverted. And the rate of producing inverted gene is reduced as the remaining non-inverted gene is reduced.





Kaist Footer