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Team:HUST-China/Modelling/DDE Model
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We solved these DDEs with R language. We also went one step further. We simulated the situation in which lag obeys a specific gaussian distribution, and the lag $\tau$changes in every certain interval. We hoped by running a random test, we could get closer to real life situation. | We solved these DDEs with R language. We also went one step further. We simulated the situation in which lag obeys a specific gaussian distribution, and the lag $\tau$changes in every certain interval. We hoped by running a random test, we could get closer to real life situation. | ||
The results are below. | The results are below. | ||
| - | + | <img src="https://static.igem.org/mediawiki/2013/e/e6/HUST_Single_araC_period.png" style="width:40px;"> | |
| - | + | <p class="small">(a) A numeric solve of AraC</p> | |
| - | + | <img src="https://static.igem.org/mediawiki/2013/e/e6/HUST_random_araC_period.png" style="width:40px;"> | |
| + | <p class="small">(b) 5 random tests numeric solve of AraC</p><br /> | ||
| + | <p class="small">Fig 1.(a)A numeric solve of AraC when lag $\tau$ = 2min, Arabinose concentration is 5%, IPTG concentration is 1mM, time interval is 0.1min. (b)numeric solve of AraC concentration versus time of 5 random tests, when Arabinose concentration is 0.7%, IPTG concentration is 10mM, and $\tau \sim (2.0,0.3^2).</p> | ||
<!----------------------------------------------Main content end------------------------------------------------------> | <!----------------------------------------------Main content end------------------------------------------------------> | ||
</div> | </div> | ||
Revision as of 13:27, 27 September 2013
DDE MODEL
Goal
To simulate how the oscillator works.
Methods
1. Establish ODE equations based on Mass-action law;
2. Investigate reasonable parameter sets from previous researches;
3. Simulation;
Results
We solved these DDEs with R language. We also went one step further. We simulated the situation in which lag obeys a specific gaussian distribution, and the lag $\tau$changes in every certain interval. We hoped by running a random test, we could get closer to real life situation.
The results are below.
2. Investigate reasonable parameter sets from previous researches;
3. Simulation;
Results
We solved these DDEs with R language. We also went one step further. We simulated the situation in which lag obeys a specific gaussian distribution, and the lag $\tau$changes in every certain interval. We hoped by running a random test, we could get closer to real life situation.
The results are below.
(a) A numeric solve of AraC
(b) 5 random tests numeric solve of AraC
Fig 1.(a)A numeric solve of AraC when lag $\tau$ = 2min, Arabinose concentration is 5%, IPTG concentration is 1mM, time interval is 0.1min. (b)numeric solve of AraC concentration versus time of 5 random tests, when Arabinose concentration is 0.7%, IPTG concentration is 10mM, and $\tau \sim (2.0,0.3^2).
Acknowledgement
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HUST-China
