http://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&feed=atom&action=historyTeam:IIT Bombay India/Modeling - Revision history2024-03-29T01:50:39ZRevision history for this page on the wikiMediaWiki 1.16.5http://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=165810&oldid=prevManishshetty: /* Analysis of multiple feedback loops */2009-10-22T02:35:45Z<p><span class="autocomment">Analysis of multiple feedback loops</span></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the '''stochastic''' process. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>2. A <ins class="diffchange diffchange-inline">'''</ins>phenomenological<ins class="diffchange diffchange-inline">''' </ins>model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the '''stochastic''' process. </div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All '''control analysis''' simulations were developed using simulink platform of MATLAB.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All '''control analysis''' simulations were developed using simulink platform of MATLAB.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A detailed summary for each of the models is provided at each of the links below.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A detailed summary for each of the models is provided at each of the links below.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/CAM|Control Analysis Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/CAM|Control Analysis Model]]</div></td></tr>
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</table>Manishshettyhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=165782&oldid=prevManishshetty: /* Analysis of multiple feedback loops */2009-10-22T02:35:08Z<p><span class="autocomment">Analysis of multiple feedback loops</span></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All <ins class="diffchange diffchange-inline">'''control analysis''' </ins>simulations were developed using simulink platform of MATLAB.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A detailed summary for each of the models is provided at each of the links below.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A detailed summary for each of the models is provided at each of the links below.</div></td></tr>
</table>Manishshettyhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=165756&oldid=prevManishshetty: /* Analysis of multiple feedback loops */2009-10-22T02:34:33Z<p><span class="autocomment">Analysis of multiple feedback loops</span></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>1. Detailed mechanistic model accounting for LacI binding to the promoter site and balance on the copy number and LacI concentration. Effect of IPTG on protein expression as measured by YFP was characterized and compared with model. Further the model was extended to represent synthesis of beta-gal expression and was related to growth on lactose. The model was able to capture the experimental observations. The simulations also indicated the burden versus growth for the various strains developed.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>1. <ins class="diffchange diffchange-inline">'''</ins>Detailed mechanistic<ins class="diffchange diffchange-inline">(deterministic) </ins>model<ins class="diffchange diffchange-inline">''' </ins>accounting for LacI binding to the promoter site and balance on the copy number and LacI concentration. Effect of IPTG on protein expression as measured by YFP was characterized and compared with model. Further the model was extended to represent synthesis of beta-gal expression and was related to growth on lactose. The model was able to capture the experimental observations. The simulations also indicated the burden versus growth for the various strains developed.</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>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the stochastic process. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the <ins class="diffchange diffchange-inline">'''</ins>stochastic<ins class="diffchange diffchange-inline">''' </ins>process. </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>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB.</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 colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">A detailed summary for each of the models is provided at each of the links below.</ins></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
</table>Manishshettyhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=165707&oldid=prevPranayiitb at 02:33, 22 October 20092009-10-22T02:33:05Z<p></p>
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</table>Pranayiitbhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=164772&oldid=prevYashpuranik: /* Analysis of multiple feedback loops */2009-10-22T02:09:17Z<p><span class="autocomment">Analysis of multiple feedback loops</span></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>We have developed models for the expression of copy number (as YFP) and lacI (as CFP) for the four constructs (zero feedback (open loop), single feedback (on copy number), single feedback (on LAcI) and double feedback (on both copy number and LacI). Three modeling strategies have been attempted.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>We have developed models for the expression of copy number (as YFP) and lacI (as CFP) for the four constructs (zero feedback (open loop), single feedback (on copy number), single feedback (on LAcI) and double feedback (on both copy number and LacI). Three modeling strategies have been attempted.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>1. Detailed mechanistic model accounting for LacI binding to the promoter site and balance on the copy number and LacI concentration. Effect of IPTG on protein expression as measured by YFP was characterized and compared with model. Further the model was extended to represent synthesis of beta-gal expression and was related to growth on lactose. The model was able to capture the experimental observations. The simulations also indicated the burden versus growth for the various strains developed.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>1. Detailed mechanistic model accounting for LacI binding to the promoter site and balance on the copy number and LacI concentration. Effect of IPTG on protein expression as measured by YFP was characterized and compared with model. Further the model was extended to represent synthesis of beta-gal expression and was related to growth on lactose. The model was able to capture the experimental observations. The simulations also indicated the burden versus growth for the various strains developed.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the stochastic process. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the stochastic process. </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize the effect of multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the multiple feedback system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
</table>Yashpuranikhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=158550&oldid=prevPranayiitb at 22:56, 21 October 20092009-10-21T22:56:25Z<p></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>== '''<del class="diffchange diffchange-inline">Stochastic modeling </del>of <del class="diffchange diffchange-inline">the laci system with </del>multiple feedback <del class="diffchange diffchange-inline">using langevin approach</del>''' ==</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>== '''<ins class="diffchange diffchange-inline">Analysis </ins>of multiple feedback <ins class="diffchange diffchange-inline">loops</ins>''' ==</div></td></tr>
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</table>Pranayiitbhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=149150&oldid=prevPranayiitb at 17:17, 21 October 20092009-10-21T17:17:51Z<p></p>
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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: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">Biological systems are known to </del>have <del class="diffchange diffchange-inline">a great degree </del>of <del class="diffchange diffchange-inline">regulation in their activity</del>, and <del class="diffchange diffchange-inline">this higher level of control is attributed </del>to the <del class="diffchange diffchange-inline">multiple levels </del>of <del class="diffchange diffchange-inline">feedback that exist within any biochemical pathway</del>. <del class="diffchange diffchange-inline">As a means </del>of <del class="diffchange diffchange-inline">gaining deeper insight within </del>the <del class="diffchange diffchange-inline">utility </del>of multiple feedback <del class="diffchange diffchange-inline">loops, we have constructed 4 strains containing plasmids with modified lac operon</del>. </div></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">'''Modeling Study'''</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 </ins>have <ins class="diffchange diffchange-inline">developed models for the expression </ins>of <ins class="diffchange diffchange-inline">copy number (as YFP) and lacI (as CFP) for the four constructs (zero feedback (open loop)</ins>, <ins class="diffchange diffchange-inline">single feedback (on copy number), single feedback (on LAcI) </ins>and <ins class="diffchange diffchange-inline">double feedback (on both copy number and LacI). Three modeling strategies have been attempted.</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">1. Detailed mechanistic model accounting for LacI binding </ins>to the <ins class="diffchange diffchange-inline">promoter site and balance on the copy number and LacI concentration. Effect </ins>of <ins class="diffchange diffchange-inline">IPTG on protein expression as measured by YFP was characterized and compared with model</ins>. <ins class="diffchange diffchange-inline">Further the model was extended to represent synthesis </ins>of <ins class="diffchange diffchange-inline">beta-gal expression and was related to growth on lactose. The model was able to capture the experimental observations. The simulations also indicated the burden versus growth for the various strains developed.</ins></div></td></tr>
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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">2. A phenomenological model was developed to represent the four constructs and langevian approach was used to estimate the variability due to the stochastic process. </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">3. The model was linearized around LacI expression and the system was represented in a block diagram to carry out the feedback analysis. Frequency response analysis using magnitude and phase Bode plots was used to characterize </ins>the <ins class="diffchange diffchange-inline">effect </ins>of <ins class="diffchange diffchange-inline">multiple feed-backs. Magnitude bode plot for the sensitivity function demonstrated that the noise was reduced for the </ins>multiple feedback <ins class="diffchange diffchange-inline">system. External white noise was introduced into the block diagram to study its effect. All simulations were developed using simulink platform of MATLAB</ins>.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
</table>Pranayiitbhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=149059&oldid=prevPranayiitb at 17:13, 21 October 20092009-10-21T17:13:36Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. </div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
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</table>Pranayiitbhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=149055&oldid=prevPranayiitb at 17:13, 21 October 20092009-10-21T17:13:26Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/DDM|Detailed Deterministic Model]]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/PSM|Phenomenological Stochastic Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/PSM|Phenomenological Stochastic Model]]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/CAM|Control Analysis Model]]</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>[[Team:IIT_Bombay_India/CAM|Control Analysis Model]]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>|</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>|</div></td></tr>
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</table>Pranayiitbhttp://2009.igem.org/wiki/index.php?title=Team:IIT_Bombay_India/Modeling&diff=149051&oldid=prevPranayiitb at 17:13, 21 October 20092009-10-21T17:13:12Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>!align="left"|</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>!align="left"|</div></td></tr>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>| <del class="diffchange diffchange-inline">Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. The lacI produced as a result of the expression can inhibit its own expression, causing one level of feedback, while it can also suppress the replication of plasmid, providing another level of control on the number of processes itself. By combination of these 2 controls, four different strains are possible. We wish to demonstrate the better control in the strain with multiple feedbacks as compared to the strain with no control by characterizing the inherent or stochastic error present in the system through simulations. Further, IPTG can bind to the lacI present in the system which would act as a repressor. Thus IPTG can act as an inducer for the system. The effects of varying concentrations of IPTG are also studied, the understanding being that a system with high IPTG concentration resembles that of an open loop system.</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>| </div></td></tr>
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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 style="color: red; font-weight: bold; text-decoration: none;">Biological systems are known to have a great degree of regulation in their activity, and this higher level of control is attributed to the multiple levels of feedback that exist within any biochemical pathway. As a means of gaining deeper insight within the utility of multiple feedback loops, we have constructed 4 strains containing plasmids with modified lac operon. </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 style="color: red; font-weight: bold; text-decoration: none;">[[Team:IIT_Bombay_India/DDM|Detailed Deterministic 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 style="color: red; font-weight: bold; text-decoration: none;">[[Team:IIT_Bombay_India/PSM|Phenomenological Stochastic 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 style="color: red; font-weight: bold; text-decoration: none;">[[Team:IIT_Bombay_India/CAM|Control Analysis Model]]</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: #ffa; color:black; font-size: smaller;"><div><del style="color: red; font-weight: bold; text-decoration: none;">Further, any genetic regulation is manifested in the phenotype observed. Since lac operon is concerned with the successful utilization of lactose, we also characterize the growth of the system on lactose. The unrestrained expression of lacI represents a burden on the system, since lactose would be taken away by the existing lacI. Thus in the strain with multiple feedbacks, since it exhibits a greater control and reduction in noise for lacI expression, we also expect it to show greater growth with lesser error. Thus, ultimately, the genetic regulation achieved on the expression of lac operon is shown to ultimately control an observed phenotype, which is the culture growth.</del></div></td><td colspan="2"> </td></tr>
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</table>Pranayiitb