Team:XMU-China/modeling

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Ordinary differential equation(s) (ODE) is one of the most popular methods in modeling. Frank R. Giordano and other scientists have introduced it exhaustively. <sup>[1]</sup> In many computational biological researching, researchers often use it to simulate the dynamics part of biological process. The concentrations of RNA, proteins, and other molecules are represented by time-dependent variables. <sup>[2]</sup> We used the same method to construct our model.</p><hr>
Ordinary differential equation(s) (ODE) is one of the most popular methods in modeling. Frank R. Giordano and other scientists have introduced it exhaustively. <sup>[1]</sup> In many computational biological researching, researchers often use it to simulate the dynamics part of biological process. The concentrations of RNA, proteins, and other molecules are represented by time-dependent variables. <sup>[2]</sup> We used the same method to construct our model.</p><hr>
<p><strong class="subtitle"><a name="Toc02" id="Toc02"></a>Modeling</strong><br>
<p><strong class="subtitle"><a name="Toc02" id="Toc02"></a>Modeling</strong><br>
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First of all, there are 4 variables and 4 parameters in this experience. Their names and meanings are listed below.<table width="250" border="0" align="center" id="commun">
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First of all, there are 4 variables and 4 parameters in this experience. Their names and meanings are listed below.<table width="740" border="0" align="center" id="commun">
   <tr>
   <tr>
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     <td width="250"><img src="https://static.igem.org/mediawiki/2012/d/d3/XMUmodel1.jpg" width="250" align="middle" ></td>
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     <td width="310"><img src="https://static.igem.org/mediawiki/2012/d/d3/XMUmodel1.jpg" width="310" align="middle" ></td>
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     <td width="250"><img src="https://static.igem.org/mediawiki/2012/6/6c/XMUmodel2.jpg" width="250" align="middle" ></td>
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     <td width="310"><img src="https://static.igem.org/mediawiki/2012/6/6c/XMUmodel2.jpg" width="430" align="middle" ></td>
   </tr>
   </tr>
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</table><br>
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<img src="https://static.igem.org/mediawiki/2012/9/9a/XmumodelPcirlt.jpg"><br>
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Those functions about describing the rate equations of biochemical reactions in the circuit P<sub>cI</sub>GLT are:<br>
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<img width="550" src="https://static.igem.org/mediawiki/2012/2/2f/XMUmodel5.jpg"><br>
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The initial condition is<br>
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<img src="https://static.igem.org/mediawiki/2012/7/74/XMUmodel6.jpg" width="180"><br>
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Equation (1) represents the course of growth of <i>E.coli.</i><sup>[3]</sup> Equation (2) represents the course of producing and decomposing GFP. OD<sub>0</sub> and flu<sub>0</sub> is value of OD and flu when t=0.
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Then, we changed the parameters and figured out the best value for fitting the data of fluorescence intensity.<br>
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<img src="https://static.igem.org/mediawiki/2012/6/69/XMUmodel3.jpg" width="300" align="middle" >
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<table width="300" border="0" align="center" id="commun">
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  <tr>
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    <td width="300"><img src="https://static.igem.org/mediawiki/2012/8/8f/XMUmodel4.jpg" width="300"  align="middle" ></td>
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  </tr>
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  <tr><td><b>Figure 1:</b> Fitting line and data of fluorescence intensity</td></tr>
</table>
</table>
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</p><hr>
 
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<br>
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<img src="https://static.igem.org/mediawiki/2012/7/74/XmumodelPbadrlt.jpg"><br>
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Those functions about describing the rate equations of biochemical reactions in the circuit P<sub>cI</sub>GLT are:<br>
 +
<img width="550" src="https://static.igem.org/mediawiki/2012/b/b7/XMUmodel11.jpg"><br>
 +
The initial condition is<br>
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<img width="180" src="https://static.igem.org/mediawiki/2012/6/68/XMUmodel12.jpg"><br>
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Equation (3) represents the course of growth of E.coli. Equation (4) represents the course of producing and decomposing GFP. Equation (5) represents the arabinose utilized for inducing. OD<sub>0</sub>, flu<sub>0</sub> and Arc0 is value of OD, flu and Arc when t=0.
 +
After that, we changed the parameters and then found out the value fitting the data of fluorescence intensity most.
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<br>
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<img src="https://static.igem.org/mediawiki/2012/c/ca/XMUmodel7.jpg" width="300" align="middle" >
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<table width="300" border="0" align="center" id="commun">
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  <tr>
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    <td width="300"><img src="https://static.igem.org/mediawiki/2012/8/8e/Xmumodel9_10.jpg" width="300"  align="middle" ></td>
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  </tr>
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  <tr><td><b>Figure 2:</b> Fitting line and data of fluorescence intensity (Value Arc=0.1).</td></tr>
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</table>
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<img src="https://static.igem.org/mediawiki/2012/6/6f/XMUmodel8.jpg" width="300" align="middle" >
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<table width="300" border="0" align="center" id="commun">
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  <tr>
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    <td width="300"><img src="https://static.igem.org/mediawiki/2012/a/a2/Xmumodel9_.jpg" width="300"  align="middle" ></td>
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  </tr>
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  <tr><td><b>Figure 2:</b> Fitting line and data of fluorescence intensity (Value Arc=0.1).</td></tr>
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</table>
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</p><hr>
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<p><strong class="subtitle"><a name="Toc03" id="Toc03"></a>Cell  Immobilization </strong><br>
 
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We have almost finished building our  display device, just a few more running tests are needed to improve and perfect  it. We plan to immobilize cells that contain other genetic circuits we  constructed and stuff them correspondingly into the seven glass tubes. The  transportation system of oxygenated medium is also needed perfection. After  some optimizing experiments, we can finally accomplish our digital display  device.&nbsp;&nbsp;&nbsp; </p><hr>
 
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<p><strong class="subtitle"><a name="Toc04" id="Toc04"></a>E-ink</strong><br>
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<p><strong class="subtitle"><a name="Toc03" id="Toc03"></a>Result</strong><br>
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  &ldquo;What will we get in this project?&rdquo;  We have been asked for many times but still  have no idea, until an E-book displayed on our lab. We were inspired by this magical  device and got our answer.</p>
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According to Figure (1-3), we can draw a conclusion that the model we constructed can simulate the process of dynamic change in fluorescence intensity. We can figure out how those parameters work in this model if we have more experience data.</p><hr>
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<p>E-book is a book-length publication in  digital form, consisting of text, images, or both, and produced on, published  through, and readable on computers or other electronic devices.[1]  Its core is E-ink. E-ink is a specific proprietary type of&nbsp;<a href="http://en.wikipedia.org/wiki/Electronic_paper" title="Electronic paper">electronic  paper</a>&nbsp;manufactured by&nbsp;<a href="http://en.wikipedia.org/wiki/E_Ink_Corporation" title="E Ink Corporation">E-Ink  Corporation</a>, founded in 1997 based on research started at the&nbsp;<a href="http://en.wikipedia.org/wiki/MIT_Media_Lab" title="MIT Media Lab">MIT Media Lab</a>.&nbsp;However,  E-ink has some shortcoming, like it just can display monochromatic figure. But,  the <em>E.coli</em> in our project in this  year can replaced the E ink. And the microcapsules, which are used for  nurturing bacteria, can also replace the pearls, which are used for carrying ink. We concluded all above for 4 reasons.</p>
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<ol>
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  <li>Digital display and E ink share  the same working principle;</li>
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  <li>There are both microcapsules on  their solution; </li>
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  <li>We can control their station by  controlling the input signal;</li>
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  <li>Comparing monochromatic E-ink,  we can construct different logical circuits in the engineering bacteria, and  add different inducer. Then the bacteria will generate chromatic GFP. In  another word, we could create multicolor E-book.</li>
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</ol>
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<p>In a word, if we can improve technology, the  digital display will probably replace the traditional E-ink.</p>
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<hr>
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<p><strong class="subtitle"><a name="Toc05" id="Toc05"></a>Reference</strong><br>
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<p><strong class="subtitle"><a name="Toc05" id="Toc05"></a>Reference</strong><br></p>
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[1]Chen, B.-S. and C.-H. Wu. A systematic design method for robust synthetic biology to satisfy design specifications[J]. BMC Systems Biology, 2009, 3(1): 66.
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<p align="left">[1] Frank R. Giordano, Maurice D. Weir, William P. Fox, A First Course in Mathematical Modeling, Third Edition,  Thomson Learning, 2003, 297-329<br>
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</p>
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  [2] RON WEISS, SUBHAYU BASU, SARA  HOOSHANGI, ABIGAIL KALMBACH, DAVID KARIG, RISHABH MEHREJA and ILKA NETRAVALI Genetic  circuit building blocks for cellular computation, communications, and signal  processing, Natural Computing, 2003, 2: 47–84. <br>
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  [3]You L, Cox RS, Weiss R, Arnold  FH. Programmed population control by cell-cell communication and regulated  killing[J]. Nature, 2004, 428(6985): 868-871. </p>
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Revision as of 23:37, 25 September 2012

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modelingindex

Contents[hide][show]
  • Introduction
    		•
  • Modeling
    		•
  • Result
  • Reference
    		•
    Model

    Model

    Introduction
    Ordinary differential equation(s) (ODE) is one of the most popular methods in modeling. Frank R. Giordano and other scientists have introduced it exhaustively. [1] In many computational biological researching, researchers often use it to simulate the dynamics part of biological process. The concentrations of RNA, proteins, and other molecules are represented by time-dependent variables. [2] We used the same method to construct our model.

    Modeling
    First of all, there are 4 variables and 4 parameters in this experience. Their names and meanings are listed below.



    Those functions about describing the rate equations of biochemical reactions in the circuit PcIGLT are:

    The initial condition is

    Equation (1) represents the course of growth of E.coli.[3] Equation (2) represents the course of producing and decomposing GFP. OD0 and flu0 is value of OD and flu when t=0. Then, we changed the parameters and figured out the best value for fitting the data of fluorescence intensity.
    Figure 1: Fitting line and data of fluorescence intensity


    Those functions about describing the rate equations of biochemical reactions in the circuit PcIGLT are:

    The initial condition is

    Equation (3) represents the course of growth of E.coli. Equation (4) represents the course of producing and decomposing GFP. Equation (5) represents the arabinose utilized for inducing. OD0, flu0 and Arc0 is value of OD, flu and Arc when t=0. After that, we changed the parameters and then found out the value fitting the data of fluorescence intensity most.
    Figure 2: Fitting line and data of fluorescence intensity (Value Arc=0.1).
    Figure 2: Fitting line and data of fluorescence intensity (Value Arc=0.1).

    Result
    According to Figure (1-3), we can draw a conclusion that the model we constructed can simulate the process of dynamic change in fluorescence intensity. We can figure out how those parameters work in this model if we have more experience data.

    Reference

    [1] Frank R. Giordano, Maurice D. Weir, William P. Fox, A First Course in Mathematical Modeling, Third Edition, Thomson Learning, 2003, 297-329
    [2] RON WEISS, SUBHAYU BASU, SARA HOOSHANGI, ABIGAIL KALMBACH, DAVID KARIG, RISHABH MEHREJA and ILKA NETRAVALI Genetic circuit building blocks for cellular computation, communications, and signal processing, Natural Computing, 2003, 2: 47–84.
    [3]You L, Cox RS, Weiss R, Arnold FH. Programmed population control by cell-cell communication and regulated killing[J]. Nature, 2004, 428(6985): 868-871.

     

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