Modeling methods

Because of the device-like nature of out project modeling plays a big part. Our model evolved from a simple matlab model to a full-blown cloudcomputing aplication parts out if intrest but also part out of necesety. This page gives an overview of some of our considerations as to building Cumulus.

First of all we have tried to decide in what enviorment we wanted 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.

COPASI

A rather comprehensive modeling package but without any visualization options. It offers extensive modeling and analysis support but nothing in the way of plotting functions or graphs. Although it would be nice to be able to use partial differential equations, its confinement to ODE´s is not a big issui.

• Matlab with SimBiology

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.

• Module 1

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.