IGEM:IMPERIAL/2008/Prototype/Drylab: Difference between revisions
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==Resources== | ==Resources== | ||
The following are four tutorials which introduce us to data analysis and modelling. The tutorials are focused on the above approach. | The following are four tutorials which introduce us to data analysis and modelling. The tutorials are focused on the above approach. MATLAB codes used for data analysis can be found in the final link. | ||
[[IGEM:IMPERIAL/2008/Modelling/Tutorial1 | Dry Lab Tutorial 1: Creating Synthetic Data]] | [[IGEM:IMPERIAL/2008/Modelling/Tutorial1 | Dry Lab Tutorial 1: Creating Synthetic Data]] | ||
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[[Media:Modelling_Growth_Curve.pdf | Dry Lab Tutorial 4: Modelling the Growth Curve]] | [[Media:Modelling_Growth_Curve.pdf | Dry Lab Tutorial 4: Modelling the Growth Curve]] | ||
[[IGEM:IMPERIAL/2008/Modelling/Tutorial1 | Dry Lab Tutorial 1: Creating Synthetic Data]] | |||
==MATLAB Codes== | ==MATLAB Codes== | ||
Revision as of 10:01, 27 August 2008
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Team Strategy
We have divided the modelling team into 3 sections:
- Modelling Genetic Circuits - Erika
- Collecting Motility Data - Yanis
- Analysis of Motlity Data and Model Fitting - Clinton & Prudence
Modelling the Genetic Circuit
A simple ODE model was assumed in order to model the concentrations of the interacting proteins.
Motility Data Collection
We plan to capture video footage of B. subtilis and analyse its motility. Using a tracking software or algorithm, we would be able to determine the position of cells of interest at each frame. From this data, we can derive the run velocity and tumbling angle at each frame.
However, it is more complicated to derive the run time and tumbling time. If, for some frames the velocity is equal to zero, we may assume that this corresponds to the tumbling phase. Therefore, we can create a new array containing the tumbling duration for each frame. The same can be done for run time. To obtain run/tumbling duration over multiple frames, we have to find a sequence of frames that corresponds to the run phase or tumbling phase, and then sum their durations to determine the duration of the run/tumbling phases.
After obtaining data arrays with run/tumbling durations, run velocity and tumbling angle, we can then proceed on to data analysis.
Video Methods
We will be using the Zeiss Axiovert 200 inverted microscope with a fully motorised stage, controlled by Improvision Volocity acquisition software. This system offers a full incubation chamber with temperature and CO2 control, a large range of filter sets from UV to far-red and a highly sensitive 1300x1000 pixel camera for fast low-light imaging.
Video images are captured into memory by the system at a basal video frame rate of 16.3Hz. This can be further increased by performing binning.
Validating the Tracking Software
For our motility analysis we will be using ImageJ (open source freeware software written by NIH). We have considered a few tracking plugins for ImageJ. The most accurate seems to be SpotTracker written by EPFL ( Ecole Polytechnique Federale de Lausanne), though not written specifically for cell tracking. Thus the need for us to validate the software and delimit its range of operability. This link leads to more on Software Validation .
Modelling the Growth of B.Subtilis
Data Analysis
Resources
The following are four tutorials which introduce us to data analysis and modelling. The tutorials are focused on the above approach. MATLAB codes used for data analysis can be found in the final link.
Dry Lab Tutorial 1: Creating Synthetic Data
Dry Lab Tutorial 2: Statistical Data Analysis
Dry Lab Tutorial 3: Testing the Tracking Software
Dry Lab Tutorial 4: Modelling the Growth Curve
Dry Lab Tutorial 1: Creating Synthetic Data
MATLAB Codes
References
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