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Team:BCCS-Bristol/Modelling
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==Modelling Strategy== | ==Modelling Strategy== | ||
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in our BSim modelling software, the aspect that we improved upon in this years release is the | in our BSim modelling software, the aspect that we improved upon in this years release is the | ||
geometric aspect of the modelling. | geometric aspect of the modelling. | ||
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===Modelling aims=== | ===Modelling aims=== | ||
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*** '''Modify BSim to allow for irregular boundaries:''' ''Currently, BSim divides space into discrete cubic blocks. This makes defining curved or spherical boundaries difficult. We are working on an algorithm to approximate curved surfaces in a cubic environment.'' | *** '''Modify BSim to allow for irregular boundaries:''' ''Currently, BSim divides space into discrete cubic blocks. This makes defining curved or spherical boundaries difficult. We are working on an algorithm to approximate curved surfaces in a cubic environment.'' | ||
** Analyse data from microscope experiments | ** Analyse data from microscope experiments | ||
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*** '''Quorum Sensing to amplify signal:''' ''The outermost bacteria in a capsule may be able to detect nitrates much more effectively than those buried deep within the capsule. If the outer bacteria signalled that they detect nitrates, the inner bacteria could detect this and express GFP. This would effectively amplify GFP expression in the capsule.'' | *** '''Quorum Sensing to amplify signal:''' ''The outermost bacteria in a capsule may be able to detect nitrates much more effectively than those buried deep within the capsule. If the outer bacteria signalled that they detect nitrates, the inner bacteria could detect this and express GFP. This would effectively amplify GFP expression in the capsule.'' | ||
*** '''Multiple populations & sensitivity:''' ''By using populations of different sensitivities, we can use the total GFP expression as a more accurate measure of the concentration of nitrates in the soil.'' | *** '''Multiple populations & sensitivity:''' ''By using populations of different sensitivities, we can use the total GFP expression as a more accurate measure of the concentration of nitrates in the soil.'' | ||
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We have been working on these areas in the last few weeks: | We have been working on these areas in the last few weeks: | ||
* Implementing boundaries and chemical fields in BSim | * Implementing boundaries and chemical fields in BSim | ||
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* GUI | * GUI | ||
* Collaborations | * Collaborations | ||
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===BSim GUI=== | ===BSim GUI=== | ||
BSim is currently an excellent modelling tool, but not widely used. By giving it a Graphical User Interface (GUI), we can make it more accessible to the wider synthetic biology community, who may lack JAVA knowledge. To help test and improve our GUI, we will make it available to several other IGEM teams. This will also constitute a modelling collaboration, which is a sufficient criterion for a gold medal. | BSim is currently an excellent modelling tool, but not widely used. By giving it a Graphical User Interface (GUI), we can make it more accessible to the wider synthetic biology community, who may lack JAVA knowledge. To help test and improve our GUI, we will make it available to several other IGEM teams. This will also constitute a modelling collaboration, which is a sufficient criterion for a gold medal. | ||
Revision as of 08:46, 27 October 2010
iGEM 2010
Contents |
Modelling Strategy
Modelling has an important role in synthetic biology. Being able to predict how a novel gene regulatory network (GRN) will behave is crucial. Before one commits the time and resources to actually constructing such a network out of BioBricks (or other pieces of genetic material) it is important to know if it is stable, if the time-scales that it operates on are relevant and if it will produce the responses that one is looking for. Many approaches exist to model GRNs, the most popular being coupled ordinary differential equations (ODEs), stochastic networks and graphical models.
For the levels of expression considered in this project the coupled ODE approach is the most valid, since it assumes that quantities of repressors, promoters, proteins etc. are high enough to be represented as being well mixed and continuous. This aspect of modelling is already well implemented in our BSim modelling software, the aspect that we improved upon in this years release is the geometric aspect of the modelling.
Modelling aims
The primary function of our modelling team is to use computational simulations to assist and inform the work of our biologists. Currently, we plan to achieve this by working on these areas:
- GRN models
- Simple GRN model (Nitrate Detector → GFP)
- Composite GRN (Detect several nutrients → Respond with a combination of signals)
- Behaviour of Capsules compared to direct application to soil (spray)
- Nitrate Diffusion into capsules and cells
- Modify BSim to allow for irregular boundaries: Currently, BSim divides space into discrete cubic blocks. This makes defining curved or spherical boundaries difficult. We are working on an algorithm to approximate curved surfaces in a cubic environment.
- Analyse data from microscope experiments
- Quorum Sensing to amplify signal: The outermost bacteria in a capsule may be able to detect nitrates much more effectively than those buried deep within the capsule. If the outer bacteria signalled that they detect nitrates, the inner bacteria could detect this and express GFP. This would effectively amplify GFP expression in the capsule.
- Multiple populations & sensitivity: By using populations of different sensitivities, we can use the total GFP expression as a more accurate measure of the concentration of nitrates in the soil.
- Constant expression of RFP, detect ratio of GFP to RFP: If our bacteria express one colour constantly, and express another colour in response to nitrate detection, the ratio of the two colours can be used to quantify the level of nitrate detection.
- Nitrate Diffusion into capsules and cells
Current activity
We have been working on these areas in the last few weeks:
- Implementing boundaries and chemical fields in BSim
- GUI
- Collaborations
BSim GUI
BSim is currently an excellent modelling tool, but not widely used. By giving it a Graphical User Interface (GUI), we can make it more accessible to the wider synthetic biology community, who may lack JAVA knowledge. To help test and improve our GUI, we will make it available to several other IGEM teams. This will also constitute a modelling collaboration, which is a sufficient criterion for a gold medal.
