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| - | <article><h2>Modeling</h2> | + | <article><h1>Modeling> |
| - | <p>We have started planning on a model on how much bacteria and other substances is needed to produce enough scent to fill up a room of arbitrary size.<p>
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| - | <h3>Cum sociis natoque penatibus et magnis dis | + | <h2>Mathematical model</h2> |
| - | parturient montes nascetur ridiculus mus</h3>
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| | + | <h3>Gene circuit </h3> |
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| - | <p>Lorem ipsum dolor sit amet, consectetuer adipiscing | + | <p>Based on our gene circuit design, we identified all the species involved in our system and factors that affect their production rates. [etc]</p> |
| - | elit. Aenean commodo ligula eget dolor. Aenean massa.
| + | |
| - | Cum sociis natoque penatibus et magnis dis parturient
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| - | montes, nascetur ridiculus mus. Donec quam felis,
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| - | ultricies nec, pellentesque eu, pretium quis, sem.</p>
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| | + | <h3>Simplifications</h3> |
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| - | <h3>Cum sociis natoque penatibus et magnis dis | + | <p>We assumed that the species identified from our gene circuit are the only ones that affect the overall concentrations in our bacterial culture. The bonding of CI is assumed to be insignificant compared to overall concentration. The model is deterministic and doesn’t take into account any noise. The phosphorylation, decay, bonding etc are assumed to be a linear function of concentration [etc] </p> |
| - | parturient montes nascetur ridiculus mus</h3>
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| | + | <h3>Equations [to be inserted]</h3> |
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| - | <p>Lorem ipsum dolor sit amet, consectetuer adipiscing
| + | YF1 |
| - | elit. Aenean commodo ligula eget dolor. Aenean massa
| + | FixJ |
| - | <strong>strong</strong>. Cum sociis natoque penatibus
| + | Phosphorylated YF1 |
| - | et magnis dis parturient montes, nascetur ridiculus
| + | Phosphorylated FixJ |
| - | mus. Donec quam felis, ultricies nec, pellentesque
| + | CI |
| - | eu, pretium quis, sem. Nulla consequat massa quis
| + | TetR |
| - | enim. Donec pede justo, fringilla vel, aliquet nec,
| + | A |
| - | vulputate eget, arcu. In enim justo, rhoncus ut,
| + | B |
| - | imperdiet a, venenatis vitae, justo. Nullam dictum
| + | C |
| - | felis eu pede <a class="external ext" href="#">link</a>
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| - | mollis pretium. Integer tincidunt. Cras dapibus.
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| - | Vivamus elementum semper nisi. Aenean vulputate
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| - | eleifend tellus. Aenean leo ligula, porttitor eu,
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| - | consequat vitae, eleifend ac, enim. Aliquam lorem ante,
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| - | dapibus in, viverra quis, feugiat a, tellus. Phasellus
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| - | viverra nulla ut metus varius laoreet. Quisque rutrum.
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| - | Aenean imperdiet. Etiam ultricies nisi vel augue.
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| - | Curabitur ullamcorper ultricies nisi.</p>
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| | + | <h3>Lights </h3> |
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| - | <h2>Developed Programs</h2> | + | <p>[Blue light affects phosphorylation] </p> |
| - | <p>We made a tool for searching through the 2014 iGEM distribution: <a href="http://igem-qsf.github.io/BioBrick-Seeker/dist/">BioBrick Seeker.</a></p> | + | <p>[Red light affects the rate of production as an idealized, completely arbitrary linear coefficient]</p> |
| - | <p>We also made a <a href="https://github.com/iGEM-QSF/igem-wiki">iGEM Wiki Quickifier.</a> that uploads a set of pages to the iGEM wiki and automatically adds all the parts common to all of them. This makes developing wiki pages easier as you can use better text editors and need to copy and paste a lot less.</p></article> | + | |
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| | + | <h2>Simulation</h2> |
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| | + | <h3>Runge-Kutta method </h3> |
| | + | |
| | + | <p>The dynamics of our system were approximated using 4th order Runge-Kutta method for the differential equations in our mathematical model [insert Runge-Kutta description]</p> |
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| | + | <h3>Parameters </h3> |
| | + | |
| | + | <p>[we used completely arbitrary estimates of actual parameters / we consulted the followin publications to obtain desider values: [insert list]] </p> |
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| | + | <h3>Software implementation </h3> |
| | + | |
| | + | <p>A computational model was created based on our mathematical model and the Runge-Kutta approximation. We made a real-time plotting function to illustrate the dynamics with each timestep. We added two light switches so that the user can have an impact on our simulation in real time. This all was then further developed into a presentable, user-friendly form that is accessible from our website. The simulation itself was developed using Python and translated into Javascript for web implementation [moar coming] </p> |
| | + | |
| | + | <h3>Accuracy </h3> |
| | + | |
| | + | <p>No noise, arbitrary parameters, simplified pathways and reaction equations -> over idealized, requires a lot of measurement of appropriate parameters and tuning to be realistic and accurate. Ideal for demonstration of our idea [insert in-depth error analysis]</p> |
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| | + | </article> |
| | </div> | | </div> |
| | </body> | | </body> |
| | </html> | | </html> |
| | {{:Team:Aalto-Helsinki/footer}} | | {{:Team:Aalto-Helsinki/footer}} |
Modeling>
Mathematical model
Gene circuit
Based on our gene circuit design, we identified all the species involved in our system and factors that affect their production rates. [etc]
Simplifications
We assumed that the species identified from our gene circuit are the only ones that affect the overall concentrations in our bacterial culture. The bonding of CI is assumed to be insignificant compared to overall concentration. The model is deterministic and doesn’t take into account any noise. The phosphorylation, decay, bonding etc are assumed to be a linear function of concentration [etc]
Equations [to be inserted]
YF1
FixJ
Phosphorylated YF1
Phosphorylated FixJ
CI
TetR
A
B
C
Lights
[Blue light affects phosphorylation]
[Red light affects the rate of production as an idealized, completely arbitrary linear coefficient]
Simulation
Runge-Kutta method
The dynamics of our system were approximated using 4th order Runge-Kutta method for the differential equations in our mathematical model [insert Runge-Kutta description]
Parameters
[we used completely arbitrary estimates of actual parameters / we consulted the followin publications to obtain desider values: [insert list]]
Software implementation
A computational model was created based on our mathematical model and the Runge-Kutta approximation. We made a real-time plotting function to illustrate the dynamics with each timestep. We added two light switches so that the user can have an impact on our simulation in real time. This all was then further developed into a presentable, user-friendly form that is accessible from our website. The simulation itself was developed using Python and translated into Javascript for web implementation [moar coming]
Accuracy
No noise, arbitrary parameters, simplified pathways and reaction equations -> over idealized, requires a lot of measurement of appropriate parameters and tuning to be realistic and accurate. Ideal for demonstration of our idea [insert in-depth error analysis]
"
