Imperial/Dry Lab/Software
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During this summer the Imperial iGEM team has developed several routines in MATLAB. We are happy to share them with the rest of Synthetic Biology Community and hope they will prove useful. | During this summer the Imperial iGEM team has developed several routines in MATLAB. We are happy to share them with the rest of Synthetic Biology Community and hope they will prove useful. | ||
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= [[Imperial/Infector_Detector/Introduction| Infector Detector]]= | = [[Imperial/Infector_Detector/Introduction| Infector Detector]]= | ||
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Numerous simulations were consequently performed on the system, for a particular set of biologically plausible parameters.<br> The routines employed in these simulations are now presented. | Numerous simulations were consequently performed on the system, for a particular set of biologically plausible parameters.<br> The routines employed in these simulations are now presented. | ||
| - | ==Simulations== | + | ==<font color=green>Simulations</font>== |
===ID_EnergyODE.m=== | ===ID_EnergyODE.m=== | ||
This function presents the vector of energy-dependent ODEs governing Infector Detector(ID). The set of representative parameters is passed globally. | This function presents the vector of energy-dependent ODEs governing Infector Detector(ID). The set of representative parameters is passed globally. | ||
| - | === | + | ===ID_Energy_CompAHL=== |
| + | This routine, simulates for a quoted set of kinetic parameters, the dynamic behaviour of the system for various input AHL concentrations. | ||
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| + | ===ID_Energy_TransferComp.m=== | ||
This script allows for user-defined simulation of the transfer functions of both system constructs, which can either be visualized independently, or simultaneously, for comparison. | This script allows for user-defined simulation of the transfer functions of both system constructs, which can either be visualized independently, or simultaneously, for comparison. | ||
The routine defines a set of parameter values and simulates the dynamic behaviour of the system by invoking the ODE set, ''ID_EnergyODE'', for use by MATLAB's ode15s solver. | The routine defines a set of parameter values and simulates the dynamic behaviour of the system by invoking the ODE set, ''ID_EnergyODE'', for use by MATLAB's ode15s solver. | ||
The transfer functions, [GFP] vs [AHL], are computed and plotted on a semi-logarithmic scale. The user maintains control over the range of [AHL] over which the computation should occur. | The transfer functions, [GFP] vs [AHL], are computed and plotted on a semi-logarithmic scale. The user maintains control over the range of [AHL] over which the computation should occur. | ||
| - | === | + | ===ID_Energy_deltaGFP=== |
A user-defined routine, performing simulations of the dynamic behaviour of the system, where the user maintains control over which inputs are to be investigated. e.g. varying initial [LuxR] of construct 2, to observe its resultant behaviour, in terms of GFP expression and/or Energy depletion. | A user-defined routine, performing simulations of the dynamic behaviour of the system, where the user maintains control over which inputs are to be investigated. e.g. varying initial [LuxR] of construct 2, to observe its resultant behaviour, in terms of GFP expression and/or Energy depletion. | ||
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====''Download ID Routines''==== | ====''Download ID Routines''==== | ||
The above routines may be downloaded together in zipped form. Please access the following link. | The above routines may be downloaded together in zipped form. Please access the following link. | ||
| - | * | + | * [https://2007.igem.org/Image:ID_simulation.zip ID Routines] |
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| + | ==<font color=green>Data Analysis</font>== | ||
| + | ===Chassis Characterisation with the Classic Promoter Model=== | ||
| + | The routine allows you to load the results of several experiments at the same time. These data are then analysed by shape matching . Once the best fit is identified, the results are returned and the corresponding graphs are plotted. | ||
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| + | * [https://2007.igem.org/Image:Chassic_Characterisation_Classic_Model.zip Chassis Characterisation with the Classic Promoter Model] | ||
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| + | ===Constitutive Synthesis of a Protein=== | ||
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| + | The experimental setup involves tagging a constitutive promoter with a fluorescent protein; the resultant fluorescence is then recorded and it is up to the user now to perform some analysis. This routine loads the experimental data as an excel sheet, allows for graphic visualization of the results, and if need be, elimination of some samples which may seem suspect (outliers). The synthesis rate and degradation term of the milieu are defined/estimated by the user. | ||
| + | The routine was developed to impart control to the user over all the operations. | ||
| + | *[https://2007.igem.org/Image:Constitutive_Promoter_Analysis.zip Constitutive Synthesis of a Protein] | ||
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| + | ===Analysis of the Degradation of a Protein=== | ||
| + | The experimental setup involves obsering the natural degradation of a fluorescent protein with a fluorometer. . This routine loads the experimental data as an excel sheet, allows for graphic visualization of the results, and if need be, elimination of some samples which may seem suspect (outliers). The degradation term of the milieu is then estimated by shape matching. The routine was developed to impart control to the user over all the operations. | ||
| + | * [https://2007.igem.org/Image:Degradation_Term_Analysis.zip Analysis of the Degradation of a Protein] | ||
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Cell-by-Date is a Temperature-Time-Integrator, which serves to expose cold-chain breaks in the propagation of highly-perishible foodstuffs, e.g. freshly ground-beef. An investigation of its behaviour was necessarily first performed by way of simulations; the following routines were employed in this process. | Cell-by-Date is a Temperature-Time-Integrator, which serves to expose cold-chain breaks in the propagation of highly-perishible foodstuffs, e.g. freshly ground-beef. An investigation of its behaviour was necessarily first performed by way of simulations; the following routines were employed in this process. | ||
| - | ==Simulations== | + | ==<font color=green>Simulations</font>== |
=== CBD_EnergyODE.m === | === CBD_EnergyODE.m === | ||
This function presents the vector of energy-dependent ODEs governing Cell-by-Date(CBD). The representative parameters are passed globally. | This function presents the vector of energy-dependent ODEs governing Cell-by-Date(CBD). The representative parameters are passed globally. | ||
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=== CBD_Sim.m=== | === CBD_Sim.m=== | ||
Here, MATLAB's ode23 is employed in the time-solution of the vector of ODEs passed by the function,''CBD_EnergyODE''. Plots of resultant GFP expression and depletion of energy(E) are generated. | Here, MATLAB's ode23 is employed in the time-solution of the vector of ODEs passed by the function,''CBD_EnergyODE''. Plots of resultant GFP expression and depletion of energy(E) are generated. | ||
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| + | ==<font color=green>Data Analysis</font>== | ||
| + | See data analysis routines for Infector Detector [[Imperial/Dry Lab/Software#Data Analysis| above]] | ||
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| + | <center> | [[Imperial/Dry_Lab | Dry Lab >>]]</center> | ||
Latest revision as of 02:43, 27 October 2007
Useful Tools
During this summer the Imperial iGEM team has developed several routines in MATLAB. We are happy to share them with the rest of Synthetic Biology Community and hope they will prove useful.
Infector Detector
In the design phase, two possible system constructs were proposed, as a solution to the problem of detecting AHL-producing biofilm.
Our modelling team established that the system is governed by a set of energy-dependent coupled ODEs, which hold true for both system constructs.
Numerous simulations were consequently performed on the system, for a particular set of biologically plausible parameters.
The routines employed in these simulations are now presented.
Simulations
ID_EnergyODE.m
This function presents the vector of energy-dependent ODEs governing Infector Detector(ID). The set of representative parameters is passed globally.
ID_Energy_CompAHL
This routine, simulates for a quoted set of kinetic parameters, the dynamic behaviour of the system for various input AHL concentrations.
ID_Energy_TransferComp.m
This script allows for user-defined simulation of the transfer functions of both system constructs, which can either be visualized independently, or simultaneously, for comparison. The routine defines a set of parameter values and simulates the dynamic behaviour of the system by invoking the ODE set, ID_EnergyODE, for use by MATLAB's ode15s solver. The transfer functions, [GFP] vs [AHL], are computed and plotted on a semi-logarithmic scale. The user maintains control over the range of [AHL] over which the computation should occur.
ID_Energy_deltaGFP
A user-defined routine, performing simulations of the dynamic behaviour of the system, where the user maintains control over which inputs are to be investigated. e.g. varying initial [LuxR] of construct 2, to observe its resultant behaviour, in terms of GFP expression and/or Energy depletion.
Download ID Routines
The above routines may be downloaded together in zipped form. Please access the following link.
Data Analysis
Chassis Characterisation with the Classic Promoter Model
The routine allows you to load the results of several experiments at the same time. These data are then analysed by shape matching . Once the best fit is identified, the results are returned and the corresponding graphs are plotted.
Constitutive Synthesis of a Protein
The experimental setup involves tagging a constitutive promoter with a fluorescent protein; the resultant fluorescence is then recorded and it is up to the user now to perform some analysis. This routine loads the experimental data as an excel sheet, allows for graphic visualization of the results, and if need be, elimination of some samples which may seem suspect (outliers). The synthesis rate and degradation term of the milieu are defined/estimated by the user. The routine was developed to impart control to the user over all the operations.
Analysis of the Degradation of a Protein
The experimental setup involves obsering the natural degradation of a fluorescent protein with a fluorometer. . This routine loads the experimental data as an excel sheet, allows for graphic visualization of the results, and if need be, elimination of some samples which may seem suspect (outliers). The degradation term of the milieu is then estimated by shape matching. The routine was developed to impart control to the user over all the operations.
Cell-by-Date
Cell-by-Date is a Temperature-Time-Integrator, which serves to expose cold-chain breaks in the propagation of highly-perishible foodstuffs, e.g. freshly ground-beef. An investigation of its behaviour was necessarily first performed by way of simulations; the following routines were employed in this process.
Simulations
CBD_EnergyODE.m
This function presents the vector of energy-dependent ODEs governing Cell-by-Date(CBD). The representative parameters are passed globally.
CBD_Sim.m
Here, MATLAB's ode23 is employed in the time-solution of the vector of ODEs passed by the function,CBD_EnergyODE. Plots of resultant GFP expression and depletion of energy(E) are generated.
Download CBD Routines
The above routines may be downloaded together in zipped form. Please access the following link.
Data Analysis
See data analysis routines for Infector Detector above
