http://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&feed=atom&action=historyTeam:KULeuven/Modeling - Revision history2024-03-29T08:32:41ZRevision history for this page on the wikiMediaWiki 1.16.5http://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=60035&oldid=prevK3n at 07:59, 4 September 20092009-09-04T07:59:19Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[image:controller_system.png|400px|right]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[image:controller_system.png|400px|right]]</div></td></tr>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>The full model consists of four parts: the blue light receptor, the comparator, the vanillin production and the vanillin receptor <del class="diffchange diffchange-inline"> </del>similar to the real world <del class="diffchange diffchange-inline">essencia </del>coli bacteria. The blue light sensor and the vanillin receptor are acting as the inputs of the system. The intensity of blue light <del class="diffchange diffchange-inline">gives </del>the wanted vanillin concentration. The vanillin receptor <del class="diffchange diffchange-inline">gives </del>the actual concentration of vanillin outside the cell. Comparing these two inputs gives us a control system for the vanillin production. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>The full model consists of four parts: the blue light receptor, the comparator, the vanillin production and the vanillin receptor<ins class="diffchange diffchange-inline">, </ins>similar to the real world <ins class="diffchange diffchange-inline">''Essencia </ins>coli<ins class="diffchange diffchange-inline">'' </ins>bacteria. The blue light sensor and the vanillin receptor are acting as the inputs of the system. The intensity of blue light <ins class="diffchange diffchange-inline">determines </ins>the wanted vanillin concentration. The vanillin receptor <ins class="diffchange diffchange-inline">records </ins>the actual concentration of vanillin outside the cell. Comparing these two inputs gives us a control system for the vanillin production. </div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== Modeling steps ==</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== Modeling steps ==</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Parameterization of the system: discover the minimal set of parameters that completely define the system.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Parameterization of the system: discover the minimal set of parameters that completely define the system.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* <del class="diffchange diffchange-inline">Foward </del>modeling: define the physical laws that, given the values of the parameters of the system, determine the value of the observable parameters.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* <ins class="diffchange diffchange-inline">Forward </ins>modeling: define the physical laws that, given the values of the parameters of the system, determine the value of the observable parameters.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Inverse modeling: given observed parameters, infer the actual parameters that produced the observed data.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Inverse modeling: given observed parameters, infer the actual parameters that produced the observed data.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* simplicity</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* simplicity</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>On the one hand, the model should serve as a reasonably close approximation to the real system, on the other hand, the model must not be overly complex <del class="diffchange diffchange-inline">so as to preclude </del>its understanding and manipulation.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>On the one hand, the model should serve as a reasonably close approximation to the real system, on the other hand, the model must not be <ins class="diffchange diffchange-inline">so </ins>overly complex <ins class="diffchange diffchange-inline">that it precludes </ins>its understanding and manipulation.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>All that's required is a high correlation between predictions and real-life performance.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>All that's required is a high correlation between predictions and real-life performance.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>We created a single cell model of interacting biochemical reacting to describe the behaviour of our 'Miss Blue Vanilla' using simbiology (Mathworks) graphical representation.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>We created a single cell model of interacting biochemical reacting to describe the behaviour of our 'Miss Blue Vanilla'<ins class="diffchange diffchange-inline">, </ins>using simbiology (Mathworks) graphical representation.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">This </del>reactions can <del class="diffchange diffchange-inline">sufficiently accurate </del>be described by Ordinary Differential Equations (ODEs) like Mass-Action laws, Hill Kinetic laws and so on.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">The </ins>reactions can <ins class="diffchange diffchange-inline"> </ins>be described <ins class="diffchange diffchange-inline">with sufficient accuracy </ins>by Ordinary Differential Equations (ODEs) like Mass-Action laws, Hill Kinetic laws and so on.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These equations are solved by a deterministic solver available in simbiology.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These equations are solved by a deterministic solver available in simbiology.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>=== Step 3: Inverse modeling ===</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>=== Step 3: Inverse modeling ===</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Although some parameters can be obtained by <del class="diffchange diffchange-inline">mining </del>the literature in a search of relevant information, </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>Although some parameters can be obtained by <ins class="diffchange diffchange-inline">digging in </ins>the literature in a search of relevant information, </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>some reactions are still not fully described or exactly known by science.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>some reactions are still not fully described or exactly known by science.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>This requires another method for obtaining the needed information<del class="diffchange diffchange-inline">, </del>inverse modeling also known as parameter estimation.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>This requires another method for obtaining the needed information<ins class="diffchange diffchange-inline">: </ins>inverse modeling also known as parameter estimation.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the first two steps are mainly deductive, this step is inductive.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the first two steps are mainly deductive, this step is inductive.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>The inverse problem consists of using the actual result of some measurements to infer the value of the parameters that <del class="diffchange diffchange-inline">characterize </del>the system.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>The inverse problem consists of using the actual result of some measurements to infer the value of the parameters that <ins class="diffchange diffchange-inline">characterizes </ins>the system.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the forward problem has (in deterministic physics) a unique solution, the inverse problem does not.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the forward problem has (in deterministic physics) a unique solution, the inverse problem does not.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The most general theory is obtained when using a probabilistic point of view, where the a priori information on the model parameters is represented by a probability distribution over the 'model space'.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The most general theory is obtained when using a probabilistic point of view, where the a priori information on the model parameters is represented by a probability distribution over the 'model space'.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Because an exhaustive search through the model space is computationally very demanding, more intelligent Monte Carlo techniques will be used<del class="diffchange diffchange-inline">, we </del>used a Metropolis-Hastings sampling algorithm.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>Because an exhaustive search through the model space is computationally very demanding, more intelligent Monte Carlo techniques will be used<ins class="diffchange diffchange-inline">. We </ins>used a Metropolis-Hastings sampling algorithm.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Notice that if one wants to resolve all the parameters in the model, a vast number of experimental data has to be obtained.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Notice that if one wants to resolve all the parameters in the model, a vast number of experimental data has to be obtained.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Most of the time we are only interested in the model that <del class="diffchange diffchange-inline">best </del>fits the observed data. This best model can be obtained by the solution of a (non linear) optimization problem. This is the main method we will use to estimate the unknown parameters <del class="diffchange diffchange-inline">is </del>the model<del class="diffchange diffchange-inline">, although </del>the probabilistic approach is more general it suffers <del class="diffchange diffchange-inline">form </del>major computational overhead.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>Most of the time we are only interested in the model that fits the observed data <ins class="diffchange diffchange-inline">best</ins>. This best model can be obtained by the solution of a (non linear) optimization problem. This is the main method we will use to estimate the unknown parameters <ins class="diffchange diffchange-inline">in </ins>the model<ins class="diffchange diffchange-inline">. Although </ins>the probabilistic approach is more general it suffers <ins class="diffchange diffchange-inline">from </ins>major computational overhead.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== References ==</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== References ==</div></td></tr>
</table>K3nhttp://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=60012&oldid=prevK3n: /* Introduction */2009-09-04T07:33:49Z<p><span class="autocomment">Introduction</span></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* the role of ordinary differential equations</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* the role of ordinary differential equations</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* modeling applied to iGEM</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* modeling applied to iGEM</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">this </del>presentation is mainly based on the presentation of last year and the wiki of ETH Zürich 2007.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">This </ins>presentation is mainly based on the presentation of last year and the wiki of ETH Zürich 2007.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>==The Full Model==</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>==The Full Model==</div></td></tr>
</table>K3nhttp://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=59304&oldid=prevK3n: /* Introduction */2009-09-03T07:12:40Z<p><span class="autocomment">Introduction</span></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== Introduction ==</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== Introduction ==</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>As an introduction to <del class="diffchange diffchange-inline">modelling </del>we made a short [https://2009.igem.org/Image:IGEMmodeling.pdf presentation]. This presentation tells about the following:</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>As an introduction to <ins class="diffchange diffchange-inline">modeling </ins>we made a short [https://2009.igem.org/Image:IGEMmodeling.pdf presentation]. This presentation tells about the following:</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* some definitions and the role of <del class="diffchange diffchange-inline">modelling</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* some definitions and the role of <ins class="diffchange diffchange-inline">modeling</ins></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* black and white box <del class="diffchange diffchange-inline">modelling</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* black and white box <ins class="diffchange diffchange-inline">modeling</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* the role of ordinary differential equations</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* the role of ordinary differential equations</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* <del class="diffchange diffchange-inline">modelling </del>applied to iGEM</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* <ins class="diffchange diffchange-inline">modeling </ins>applied to iGEM</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>this presentation is mainly based on the presentation of last year and the wiki of ETH Zürich 2007.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>this presentation is mainly based on the presentation of last year and the wiki of ETH Zürich 2007.</div></td></tr>
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</table>K3nhttp://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=59303&oldid=prevK3n: /* Modelling steps */2009-09-03T07:12:00Z<p><span class="autocomment">Modelling steps</span></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The full model consists of four parts: the blue light receptor, the comparator, the vanillin production and the vanillin receptor similar to the real world essencia coli bacteria. The blue light sensor and the vanillin receptor are acting as the inputs of the system. The intensity of blue light gives the wanted vanillin concentration. The vanillin receptor gives the actual concentration of vanillin outside the cell. Comparing these two inputs gives us a control system for the vanillin production. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The full model consists of four parts: the blue light receptor, the comparator, the vanillin production and the vanillin receptor similar to the real world essencia coli bacteria. The blue light sensor and the vanillin receptor are acting as the inputs of the system. The intensity of blue light gives the wanted vanillin concentration. The vanillin receptor gives the actual concentration of vanillin outside the cell. Comparing these two inputs gives us a control system for the vanillin production. </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>== <del class="diffchange diffchange-inline">Modelling </del>steps ==</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>== <ins class="diffchange diffchange-inline">Modeling </ins>steps ==</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The scientific procedure for the study of a physical system can be divided in the following 3 steps</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The scientific procedure for the study of a physical system can be divided in the following 3 steps</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Parameterization of the system: discover the minimal set of parameters that completely define the system.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>* Parameterization of the system: discover the minimal set of parameters that completely define the system.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* Foward <del class="diffchange diffchange-inline">modelling</del>: define the physical laws that, given the values of the parameters of the system, determine the value of the observable parameters.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* Foward <ins class="diffchange diffchange-inline">modeling</ins>: define the physical laws that, given the values of the parameters of the system, determine the value of the observable parameters.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>* Inverse <del class="diffchange diffchange-inline">modelling</del>: given observed parameters, infer the actual parameters that produced the observed data.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>* Inverse <ins class="diffchange diffchange-inline">modeling</ins>: given observed parameters, infer the actual parameters that produced the observed data.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Most of the time this is an iterative approach, the last step will contain an indication of how good the model </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Most of the time this is an iterative approach, the last step will contain an indication of how good the model </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>fits the observed data. Sometimes it will be necessary to adjust the proposed model.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>fits the observed data. Sometimes it will be necessary to adjust the proposed model.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>=== Step 1 and 2: <del class="diffchange diffchange-inline">Modelling </del>and simulation===</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>=== Step 1 and 2: <ins class="diffchange diffchange-inline">Modeling </ins>and simulation===</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>By a model, we mean an abstraction of some real system that can be used to obtain predictions and formulate control strategies.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>By a model, we mean an abstraction of some real system that can be used to obtain predictions and formulate control strategies.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These equations are solved by a deterministic solver available in simbiology.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These equations are solved by a deterministic solver available in simbiology.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>=== Step 3: Inverse <del class="diffchange diffchange-inline">modelling </del>===</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>=== Step 3: Inverse <ins class="diffchange diffchange-inline">modeling </ins>===</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Although some parameters can be obtained by mining the literature in a search of relevant information, </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Although some parameters can be obtained by mining the literature in a search of relevant information, </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>some reactions are still not fully described or exactly known by science.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>some reactions are still not fully described or exactly known by science.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>This requires another method for obtaining the needed information, inverse <del class="diffchange diffchange-inline">modelling </del>also known as parameter estimation.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>This requires another method for obtaining the needed information, inverse <ins class="diffchange diffchange-inline">modeling </ins>also known as parameter estimation.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the first two steps are mainly deductive, this step is inductive.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>While the first two steps are mainly deductive, this step is inductive.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Most of the time we are only interested in the model that best fits the observed data. This best model can be obtained by the solution of a (non linear) optimization problem. This is the main method we will use to estimate the unknown parameters is the model, although the probabilistic approach is more general it suffers form major computational overhead.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Most of the time we are only interested in the model that best fits the observed data. This best model can be obtained by the solution of a (non linear) optimization problem. This is the main method we will use to estimate the unknown parameters is the model, although the probabilistic approach is more general it suffers form major computational overhead.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== References ==</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>== References ==</div></td></tr>
</table>K3nhttp://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=55592&oldid=prevBart Bosmans at 14:28, 28 August 20092009-08-28T14:28:00Z<p></p>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">__NOTOC__</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">== Introduction ==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">As an introduction to modelling we made a short [https://2009.igem.org/Image:IGEMmodeling.pdf presentation]. This presentation tells about the following:</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* some definitions and the role of modelling</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* black and white box modelling</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* the role of ordinary differential equations</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* modelling applied to iGEM</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">this presentation is mainly based on the presentation of last year and the wiki of ETH Zürich 2007.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">==The Full Model==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">[[image:controller_system.png|400px|right]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">The full model consists of four parts: the blue light receptor, the comparator, the vanillin production and the vanillin receptor similar to the real world essencia coli bacteria. The blue light sensor and the vanillin receptor are acting as the inputs of the system. The intensity of blue light gives the wanted vanillin concentration. The vanillin receptor gives the actual concentration of vanillin outside the cell. Comparing these two inputs gives us a control system for the vanillin production. </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">== Modelling steps ==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">The scientific procedure for the study of a physical system can be divided in the following 3 steps</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* Parameterization of the system: discover the minimal set of parameters that completely define the system.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* Foward modelling: define the physical laws that, given the values of the parameters of the system, determine the value of the observable parameters.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* Inverse modelling: given observed parameters, infer the actual parameters that produced the observed data.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">Most of the time this is an iterative approach, the last step will contain an indication of how good the model </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">fits the observed data. Sometimes it will be necessary to adjust the proposed model.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">=== Step 1 and 2: Modelling and simulation===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">By a model, we mean an abstraction of some real system that can be used to obtain predictions and formulate control strategies.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">In order to be useful, a model must necessarily incorporate elements of two conflicting attributes:</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* realism</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">* simplicity</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">On the one hand, the model should serve as a reasonably close approximation to the real system, on the other hand, the model must not be overly complex so as to preclude its understanding and manipulation.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">All that's required is a high correlation between predictions and real-life performance.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">We created a single cell model of interacting biochemical reacting to describe the behaviour of our 'Miss Blue Vanilla' using simbiology (Mathworks) graphical representation.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">This reactions can sufficiently accurate be described by Ordinary Differential Equations (ODEs) like Mass-Action laws, Hill Kinetic laws and so on.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">These equations are solved by a deterministic solver available in simbiology.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">=== Step 3: Inverse modelling ===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">Although some parameters can be obtained by mining the literature in a search of relevant information, </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">some reactions are still not fully described or exactly known by science.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">This requires another method for obtaining the needed information, inverse modelling also known as parameter estimation.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">While the first two steps are mainly deductive, this step is inductive.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">The inverse problem consists of using the actual result of some measurements to infer the value of the parameters that characterize the system.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">While the forward problem has (in deterministic physics) a unique solution, the inverse problem does not.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">The most general theory is obtained when using a probabilistic point of view, where the a priori information on the model parameters is represented by a probability distribution over the 'model space'.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">Because an exhaustive search through the model space is computationally very demanding, more intelligent Monte Carlo techniques will be used, we used a Metropolis-Hastings sampling algorithm.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">Notice that if one wants to resolve all the parameters in the model, a vast number of experimental data has to be obtained.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">Most of the time we are only interested in the model that best fits the observed data. This best model can be obtained by the solution of a (non linear) optimization problem. This is the main method we will use to estimate the unknown parameters is the model, although the probabilistic approach is more general it suffers form major computational overhead.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">== References ==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">"Inverse problem theory and methods for model parameter estimation", Albert Tarantola <br\></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">"Modern simulation and modeling", Reuven Y. Rubinstein, Benjamin Melamed</ins></div></td></tr>
</table>Bart Bosmanshttp://2009.igem.org/wiki/index.php?title=Team:KULeuven/Modeling&diff=737&oldid=prevIGEM HQ: Prototype team page2009-03-26T15:17:00Z<p>Prototype team page</p>
<p><b>New page</b></p><div>No Page Text</div>IGEM HQ