Team:BCCS-Bristol/Modeling/BSim

From 2009.igem.org

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== BSim stochastic simulation etc==
== BSim stochastic simulation etc==
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= BSim Features =
 +
 
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In this section we outline the main features available in BSim 2009.
 +
 
 +
 
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== Biological Simulation Features ==
 +
 
 +
=== Bacteria ===
 +
 
 +
* Heavy basis on literature
 +
* Run and tumble by default (flagellar motor)
 +
* chemotaxis!
 +
* brownian motion and fluid forces implemented
 +
* easily adaptable.
 +
 
 +
=== Interactions and actions ===
 +
* easily specified and adaptable
 +
* can do whatever you want:
 +
** Collision
 +
** Merging (vesicle/bacterium)
 +
** GRNs
 +
* other interactions:
 +
** Everything can interact! chemical fields, GRNs, vesicles...
 +
 
 +
=== Vesicles ===
 +
 
 +
* Small, but size based on growth
 +
* Size and creation rate based on rate of change of surface area [ref - steve?]
 +
* Vesicle movement - brownian motion in a viscous fluid environment
 +
* Interaction can be specified
 +
 
 +
=== Chemical Fields ===
 +
 
 +
* diffusion
 +
* decay
 +
* physical units
 +
 
 +
=== GRN modelling ===
 +
 
 +
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.
 +
 
 +
=== [[Team:BCCS-Bristol/Modeling/Magnetotaxis|Magnetotaxis]] ===
 +
 
 +
Summary of magnetotaxis here with image etc.
 +
 
 +
==References:==
 +
 
 +
[1] http://www.calpoly.edu/~rfrankel/magbac101.html
 +
 
 +
[2] Blakemore, RP (1982) Magnetotactic bacteria. Annual Reviews of Microbiology 36: 217-238.
 +
 
 +
[3] Nicola Ann Spaldin, Magnetic materials: fundamentals and device applications, University Press, Cambridge 2003

Revision as of 19:54, 18 October 2009

BCCS-Bristol
iGEM 2009



Read more about BSim, our Stochastic agent based modelling framework.


Tutorials
Download
Case Studies
Interested in finding out more about the creation of BSim simulations? Click here for a selection of tutorial examples. Want to use the BSim software yourself? Click here to download the core libraries and source code (available freely under the MIT licence). The BSim platform has already been used in a number of other projects! Read more about these projects here.


Contents

BSim stochastic simulation etc

BSim Features

In this section we outline the main features available in BSim 2009.


Biological Simulation Features

Bacteria

  • Heavy basis on literature
  • Run and tumble by default (flagellar motor)
  • chemotaxis!
  • brownian motion and fluid forces implemented
  • easily adaptable.

Interactions and actions

  • easily specified and adaptable
  • can do whatever you want:
    • Collision
    • Merging (vesicle/bacterium)
    • GRNs
  • other interactions:
    • Everything can interact! chemical fields, GRNs, vesicles...

Vesicles

  • Small, but size based on growth
  • Size and creation rate based on rate of change of surface area [ref - steve?]
  • Vesicle movement - brownian motion in a viscous fluid environment
  • Interaction can be specified

Chemical Fields

  • diffusion
  • decay
  • physical units

GRN modelling

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 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.

Magnetotaxis

Summary of magnetotaxis here with image etc.

References:

[1] http://www.calpoly.edu/~rfrankel/magbac101.html

[2] Blakemore, RP (1982) Magnetotactic bacteria. Annual Reviews of Microbiology 36: 217-238.

[3] Nicola Ann Spaldin, Magnetic materials: fundamentals and device applications, University Press, Cambridge 2003

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