From 2009.igem.org
(Difference between revisions)
|
|
| (One intermediate revision not shown) |
| Line 1: |
Line 1: |
| - | {{:Team:BCCS-Bristol/Header}}
| |
| | | | |
| - | =GRN Modelling in BSim=
| |
| - |
| |
| - | BSim 2008: "Each of the modelling approaches [''GRNs and agent-based modelling''] have been considered in separate contexts, mainly due to the differing aspects of the system they are concerned with. Now, having working models for each, it would be possible to bring these together with the aim of improving simulation accuracy and allowing for the internal cellular dynamics to be studied in an ever changing physical environment. Such a hybrid model may also help shed light on the critical aspects of project as a whole."
| |
| - |
| |
| - | BSim 2009 provides a robust implementation of the second and fourth order Runge-Kutta methods for systems of ordinary differential equations. It is possible to easily specify systems of ODEs as objects within the simulation. These ODE systems can be "attached" to objects in the simulation if necessary and can be used to simulate any aspect of the environment to which they are coupled, depending on the user's requirements. An example would be attaching an ODE system to each bacterium and coupling these systems via an external chemical field. See the overview of our ongoing [[Team:BCCS-Bristol/Modeling/quorum_coupled_repressilators|quorum-coupled repressilators]] simulation for an example application of this.
| |
| - |
| |
| - | As a result of the modular nature of the solver implementation it would also be possible to implement stochastic ODEs, and delay differential equations in a similar manner. These features are likely to be implemented soon to assist with the modelling of more complex GRN systems across a population.
| |
Latest revision as of 00:17, 21 October 2009
"
