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Team:KAIST Korea/Project Modeling
From 2012.igem.org
2012 KAIST Korea
Mail : kaist.igem.2012@gmail.com
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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.
