Team:Newcastle/Modelling/BioNetGen

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The software we primarily modelled with, BioNetGen, is very intuitive to work with and very powerful. However prior to this year it has only been used [https://2013.igem.org/Team:Leeds/Modeling by one other iGEM team]. Therefore we gave a [https://2013.igem.org/Team:Newcastle/Outreach/Workshop workshop] on using BioNetGen to the other UK iGEM teams, which inspired another team to use the software. We also recorded an introductory video for modelling in BioNetGen using the Graphical User Interface - [http://rulebender.cs.pitt.edu/wordpress/ Rulebender], which can be found below. This video was also for a collaboration with the Manchester iGEM team for their introduction to modelling project.
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BioNetGen is an example of rule based modelling (the only other commonly used example being [http://www.kappalanguage.org Kappa]). In this we state a series of 'reaction rules' which specify what reactions can occur and at what rates. The same model can be simulated in two different modes (deterministically (using differential equations) or stochastically (using the Gillespie algorithm). Molecules are given 'domains' that represent binding sites to other domains, allowing the formation of complexes. A domain can also represent a site that can exist in multiple states, for example a site which can be ''phosphorylated'' and ''dephosphorylated''. These features are unique to rule based modelling, and reduce the number of reactions that need to be written without sacrificing complexity. Furthermore we do not need to write any differential equations on the propensity functions for the Gillespie algorithm. Our reaction rules with rates are automatically converted by BioNetGen.
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The Manchester iGEM teams introduction to modelling project can be found [https://2013.igem.org/Team:Manchester/Collaboration here]
{{Team:Newcastle/Sponsors}}
{{Team:Newcastle/Sponsors}}

Latest revision as of 22:56, 4 October 2013

 
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BioNetGen

The software we primarily modelled with, BioNetGen, is very intuitive to work with and very powerful. However prior to this year it has only been used by one other iGEM team. Therefore we gave a workshop on using BioNetGen to the other UK iGEM teams, which inspired another team to use the software. We also recorded an introductory video for modelling in BioNetGen using the Graphical User Interface - [http://rulebender.cs.pitt.edu/wordpress/ Rulebender], which can be found below. This video was also for a collaboration with the Manchester iGEM team for their introduction to modelling project.

BioNetGen is an example of rule based modelling (the only other commonly used example being [http://www.kappalanguage.org Kappa]). In this we state a series of 'reaction rules' which specify what reactions can occur and at what rates. The same model can be simulated in two different modes (deterministically (using differential equations) or stochastically (using the Gillespie algorithm). Molecules are given 'domains' that represent binding sites to other domains, allowing the formation of complexes. A domain can also represent a site that can exist in multiple states, for example a site which can be phosphorylated and dephosphorylated. These features are unique to rule based modelling, and reduce the number of reactions that need to be written without sacrificing complexity. Furthermore we do not need to write any differential equations on the propensity functions for the Gillespie algorithm. Our reaction rules with rates are automatically converted by BioNetGen.

The Manchester iGEM teams introduction to modelling project can be found here

Newcastle University The Centre for Bacterial Cell Biology Newcastle Biomedicine The School of Computing Science The School of Computing Science