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Latest revision as of 01:56, 22 September 2011

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A brief introduction to modelling

Step by step guide on how we generated our model for the project, explained in a way that even a biologist could understand!

Hi everyone,
We're the University of Glasgow iGEM Team 2011 and we decided to write this short tutorial, or set of tips and advice if you prefer, to help you with your future experiments. First of all, to avoid any disappointments, let's clarify what modelling actually is: it's creating a mathematical model of the system you're going to work on and predicting its behaviour prior to testing it experimentally. It is a very useful way of saving time and resources on repetitions of the same experiment in order to optimise conditions for it. Instead you just need to do a bit of research and a few calculations, and the model should be able to predict the outcome. This tutorial will go step by step over principles of modelling and each step will be backed-up with an examples from our work. Let's do it.

Firstly, sit down and think how the system actually works and what it supposed to do. Sounds trivial, but it's probably the most important step. Look up the details. Google Scholar is a great tool for that. We were working on biofilms and their dispersion. Therefore, we needed molecules and proteins able to do that. You don't need exact matches. Sometimes something similar is just fine. I need to warn you though, you're going to need a lot of patience. Also, I'd suggest to meet with somebody who has some experience with modelling, to show you right path.

When you figure out the details of the system, let's think about what kind of equation you need for your model. Our main questions were “how fast do our molecules move through a biofilm?” and “if we trigger the dispersion at a certain point, how big an area would be affected?”. For that we needed a diffusion equation in some easy form. While looking for the appropriate equation, don't get scared or discouraged. Usually, when you find a tutorial for some equation, they show you how it was derived. That's the part that is scary-looking, overcomplicated and completely irrelevant. At the bottom you usually find a fully derived, quite easy-looking equation that will be actually useful to you. It took some time, but eventually I found a diffusion equation for two-dimensional diffusion of molecules in a kind of 'plug and play' form.

Then, you need to find the details to put into the equation. We needed to do research on all the relevant molecules individually. Required details were: diffusion coefficient, critical concentration and translation rate for all of them. That takes the longest, I guess. Moreover, some of them require some 'editing'. For example, to get a translation rate of molecules, I needed to find out how many amino acids there are in each molecule, then on average how many codons are translated per second by E. coli and how many ribosomes E. coli possesses. Then I divided number of ribosomes by total number of translated proteins in the bug. That gave us how many ribosomes on average work on a single protein.

Finally, you need some program to calculate the whole thing. For us, an Excel-like program was sufficient. Here you combine all the pieces together: type in the equation as a formula and recalculate the numbers to the appropriate units. The software will do rest of the work. Now the only things left to do are to read out the data you just obtained and make some fancy-looking figures. For that we suggest GNUplot, even though it takes some time to learn how to use it. Don't be overconfident: if some numbers look funny or unconvincing, go over the maths parts again – there might be something wrong, such as missing brackets. Sometimes a graph can help you visualise if the model behaves as you expected. When finally everything looks right, you're all done. Congratulations.

Some important tips: remember not to overcomplicate the model. It is just a model to help you design and test the system by giving you a rough estimation. In the end, you can improve the model with experimental data. Also, whenever you're stuck, speak to other people. Somebody else might have an idea how to push the work forward. If it's possible, contact somebody with experience with modelling. They can help quite a lot, especially with technical stuff such as picking the right equations. Moreover, always take a note or save a source for where you took the supporting information from. Referencing is a vital part of every scientific project. All the data regarding our project you can check out on our WIKI (https://2011.igem.org/Team:Glasgow)

That's all. I hope it helped at least a little bit. Now get to work. At the times of crisis, remember that in the end it's really satisfying to see the whole thing working. The University of Glasgow iGEM Team 2011 wishes you the best of luck and a lot of patience.