Team:Edinburgh/Results

From 2010.igem.org

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<p>The main result achieved by the modelling component of our project was the theoretical conclusion that, given the information available and the assumptions made, the biological systems proposed throughout our project should work. The genomic BRIDGEs model provided verification of the time course of the BRIDGE protocol. The intracellular bacterial BRIDGEs model acted to verify the idea of a light-based repressilating system, and to confirm that the responses of the various light pathways were as expected. Finally, the intercellular bacterial BRIDGEs model established the concept of light-based communication within colonies of cells, in all its complexity.</p>
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<p>The main <b>result</b> achieved by the modelling component of our project was the theoretical <b>conclusion</b> that, given the <b>information</b> available and the <b>assumptions</b> made, the biological systems <b>proposed</b> throughout our project should work. The <a href="http://2010.igem.org/Team:Edinburgh/Modelling/Genomic">genomic BRIDGEs model</a> provided <b>verification</b> of the time course of the <a href="http://2010.igem.org/Team:Edinburgh/Project/Protocol">BRIDGE protocol</a>. The <a href="http://2010.igem.org/Team:Edinburgh/Modelling/Bacterial">intracellular bacterial BRIDGEs model</a> acted to verify the idea of a <a href="http://2010.igem.org/Team:Edinburgh/Bacterial/Core_repressilator">light-based repressilating system</a>, and to confirm that the responses of the <a href="http://2010.igem.org/Team:Edinburgh/Modelling/Bacterial">various light pathways</a> were as expected. Finally, the <a href="http://2010.igem.org/Team:Edinburgh/Modelling/Signalling">intercellular bacterial BRIDGEs model</a> established the concept of light-based communication within colonies of cells, in all its <b>complexity</b>.</p>
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<p>Each of the above models was extensively analysed via a variety of methods available, in an attempt to push the boundaries of understanding regarding the biological processes embodied. Some interesting results were revealed, but this extensive analysis did much to reinforce the conclusion made above - that theoretically, our systems should work!</p>
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<p>Each of the above models was extensively <b>analysed</b> via a variety of <b>methods</b> available, in an attempt to <b>push the boundaries</b> of <b>understanding</b> regarding the biological processes <b>embodied</b> within. Some interesting <b>results</b> were revealed, but overall this extensive analysis did much to <b>reinforce</b> the conclusion made above - that theoretically, our systems should work!</p>
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<p>Throughout the process, Ty Thomson's framework for modelling BioBricks in Kappa was found to be an invaluable aid in organising and thoroughly describing the biological parts involved. Whether in simply ensuring that the entirety of the BioBrick's actions were described, or in making explicit the correlation of various rate parameters to their effects upon the model, the usefulness of such a structured and standardised framework in developing biological models cannot be understated.</p>
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<p>Throughout the process, Ty Thomson's <b>framework</b> for modelling BioBricks in Kappa was found to be an <b>invaluable</b> aid in <b>organising</b> and <b>thoroughly describing</b> the biological parts involved. Whether in simply <b>ensuring</b> that the entirety of the BioBrick's actions were <b>described</b>, or in making <b>explicit</b> the <b>correlation</b> between various rate parameters and their <b>effects</b> upon the model, the usefulness of such a <b>structured</b> and <b>standardised</b> framework in developing biological models cannot be <b>understated</b>.</p>
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<p>One final result that hopefully was achieved by our modelling is the establishment and promotion of Kappa as a BioBrick-friendly modelling language and alternative to traditional methods of modelling such as differential equations. From its introduction to iGEM by last year's Edinburgh team, this year its use has spread to a handful of other teams as well... we are hopeful that this trend will continue in the near future, due to the numerous advantages that are inherent in the approach.</p>
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<p>One final result that hopefully was achieved by our modelling is the <b>establishment</b> and <b>promotion</b> of <a href="http://2010.igem.org/Team:Edinburgh/Modelling/Kappa">the Kappa stochastic rule-based modelling language</a> as a <b>BioBrick-friendly alternative</b> to traditional methods of modelling such as differential equations. From its <b>introduction</b> to iGEM by last year's Edinburgh team, this year its use has <b>spread</b> to a handful of other teams as well... we are hopeful that this <b>trend</b> will continue in the near future, due to the numerous <b>advantages</b> that are inherent in the approach.</p>
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Revision as of 12:02, 7 October 2010







Project Results


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Results: Genomic BRIDGEs


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Results: Bacterial BRIDGEs


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Results: Modelling BRIDGEs


The main result achieved by the modelling component of our project was the theoretical conclusion that, given the information available and the assumptions made, the biological systems proposed throughout our project should work. The genomic BRIDGEs model provided verification of the time course of the BRIDGE protocol. The intracellular bacterial BRIDGEs model acted to verify the idea of a light-based repressilating system, and to confirm that the responses of the various light pathways were as expected. Finally, the intercellular bacterial BRIDGEs model established the concept of light-based communication within colonies of cells, in all its complexity.

Each of the above models was extensively analysed via a variety of methods available, in an attempt to push the boundaries of understanding regarding the biological processes embodied within. Some interesting results were revealed, but overall this extensive analysis did much to reinforce the conclusion made above - that theoretically, our systems should work!

Throughout the process, Ty Thomson's framework for modelling BioBricks in Kappa was found to be an invaluable aid in organising and thoroughly describing the biological parts involved. Whether in simply ensuring that the entirety of the BioBrick's actions were described, or in making explicit the correlation between various rate parameters and their effects upon the model, the usefulness of such a structured and standardised framework in developing biological models cannot be understated.

One final result that hopefully was achieved by our modelling is the establishment and promotion of the Kappa stochastic rule-based modelling language as a BioBrick-friendly alternative to traditional methods of modelling such as differential equations. From its introduction to iGEM by last year's Edinburgh team, this year its use has spread to a handful of other teams as well... we are hopeful that this trend will continue in the near future, due to the numerous advantages that are inherent in the approach.



Results: Human BRIDGEs


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Results: In conclusion


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