Difference between revisions of "Team:Manchester/Model"
Huiwenchong (Talk | contribs) |
Mtdavies1995 (Talk | contribs) |
||
| Line 243: | Line 243: | ||
<center> | <center> | ||
<p style="font-size:1.2em;"> | <p style="font-size:1.2em;"> | ||
| − | We found great inspiration from our <a href="https://2016.igem.org/Team:Manchester/Human_Practices/Industries#mec">human practices</a> and guidance working both ways | + | We found great inspiration from our <a href="https://2016.igem.org/Team:Manchester/Human_Practices/Industries#mec">human practices</a> and guidance working both ways with the experiments. Click <a href="https://2016.igem.org/Team:Manchester/Model/hp"> here</a> to see a summary. |
</p> | </p> | ||
</center> | </center> | ||
Revision as of 23:35, 17 October 2016
Welcome to our modelling section. We have used a novel ensemble modeling approach, to better aid the synergy between wetalb and dry lab teams. On this page you will find short answers to the questions; What is ensemble modelling? What did we model? what did our model achieve?
For navigating the Wiki you need to know that the sections on results and human practice/lab integration can be accessed in the menu bar.
Part of what we hope to achieve with this ensemble methodology is a blueprint for other iGEM teams. As such each step in creating and using our model is laid out in the below diagram. Clicking on a specific step will take you to a page explaining the theory. Going deeper you can access a discussion of the code. There will be a link to the relevant parts of our github (a website storing our code) Use these codes as you wish.
Link to github homepage
What were we modelling?
We focused on modelling the Cell-free Mechanism, see the experimental section for details. The short version is the AlcoPatch relies on alcohol, alcohol oxidase (AOx), horseradish peroxidase (HRP) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) which are mixed together producing oxidised ABTS which is colourful. The ensemble modelling process will work for any model however and this was chosen as a simpler example to demonstrate the technique, focusing on the process rather than the system itself.
Due to time constraints the modelling was based on an analogous system of glucose and glucose oxidase (GOx) rather than alcohol and AOx, this was chosen as the reaction network is the same and it links in with the suggestions given at the Microbiology Society Conference in the human practices that the design need not be limited for alcohol but could be used by diabetics, etc if used to detect other molecules in sweat. While the equivalent analysis was done for glucose. Rerunning the analysis for alcohol would only require the change of some constants, so the analysis acts as a sufficient proof of concept and still shows the integration of human practices.
A schematic diagram of the final scheme is given below. For more information about the steps click on the blue enzyme boxes.
Alternatively you can click on the enzyme name below:
What is Ensemble Modelling?
Instead of running your model once with some specific parameters (i.e rate constants), you find all the possible parameters in literature and run your model for lots of combinations sampled in a clever way. By doing this you take take into account the uncertainty in the parameters. You will create probabilistic outputs allowing you to make rigorous conclusions.
Following through our flow diagram blueprint should make this concept clear.
What did our model achieve?
Regardless how clever, interesting or unique a model is ultimately all that matters is the results at the end. We had 2 main aims for our outputs: improving our understanding of our system and answering key questions that arouse during the Human Practices.
To improve our knowledge of the system we undertook 2 main analyses: Improving our understanding the reaction network mechanism Investigating the relationships between the parameters in our system To answer the questions from the human practices there was 1 main analysis: Costing the AlcoPatch Further justification for why these were chosen is given on the respective pages.
We found great inspiration from our human practices and guidance working both ways with the experiments. Click here to see a summary.
