Team:Groningen/modeling methods
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- | + | ''Because of the device-like nature of out project modeling plays a big part. This page gives an overview of some of our organistional considerations and provides links to the more practical aspects. A big consideration is that our modeling team comes from the local Artifitial Inteligence (AI) department and has significant experience in modeling in matlab.'' | |
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==Methods== | ==Methods== |
Revision as of 15:26, 21 September 2011
Modeling methods
Because of the device-like nature of out project modeling plays a big part. This page gives an overview of some of our organistional considerations and provides links to the more practical aspects. A big consideration is that our modeling team comes from the local Artifitial Inteligence (AI) department and has significant experience in modeling in matlab.
Methods
First of all we have to decide in what enviorment we want to model in. There is a lot of different software out there. Our 2009 team did a large survey on modeling packages used in Igem [1]. Our whitebook (information from previous teams)also included several biomodeling packages that we should look at:
SynBioSS
SynBioSS features a gui implemted in python and can interface with most mayor other modeling frameworks such as SBML, Hy3S as NetCDF. It does not have a good visualisation interface and suggest you load your results into matlab for examination. SynBioSS also includes a supercomputer Message Passing Interface implementation which is nice if you want to go all out on some sort of cluster achitecture. Unfortunately SynBioSS is instable, does not support 64 bit achitectures and nobody has worked on it since 2010. So for us this is not an option. SynBioSS can be found at [http://synbioss.sourceforge.net/simulator/]
CellDesigner|CellDesigner
CellDesigner is graphical simulation package that can model simple cellular mechanics that is pretty but not very usefull. While it has a superb graph and network drawing options. It has relativly limited visualisation options for simulations. It biggest shortcomming is that the mathematics that can be used to define the reaction speeds are rather limited. There are no options for stogastic implementations so checking the robustness of your circiut will be a tedious process.
Although COPASI and SimBiology seemed really nice (be sure to look at it when in doubt) we decided to go with matlab for the following reasons:
- Freedom of programming: Although the matlab programming syntax is rather cumborsome (espcially when using OOP) we are sure it can produce anything we want.
- Popularety: There is a very large userbase for matlab and plenty of support for it. Many other iGEM teams use it so it will be easy to share our finings and models.
- Great plotting and visalisation option: this will allow us to see what is going on without the hassle of exporting and importing the data to other packages.
- Familiarety of the team: Not having to learn using a program from the beginning is a big advantage. Some of our members have years of experience with matlab and have no problem implementing anything in matlab.
Library
We are currently developing our own modeling library and hopefully we will be able to finish it in time for other teams to use it. It will be geared towards beginning/intermediate matlab users who want to model single cell processes.
Modules
We decided to build our model in the samen modules as the cloners will use. Because of the fragilety of the by stable switches these should be modeled first.
Modeling blog
You can check our modeling progress on our modeling blog. This will contain weekly updates of our progress and some highligths of our results.