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| 5. Add `Analysis` directory to path and import necessary modules | 5. Read model. The name of the main model file is `A.woodii.spy`. Recall from previous practicals and read this model. |
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| 6. Add `Analysis` directory to path and import necessary modules . import BuildLP . |
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| . import BuildLP | . |
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| 6. Read model. The name of the main model file is `A.woodii.spy`. Recall from previous practicals and read this model. | 7. We will now create a LP problem from this model. We would make the LP such that its objective function is minimization of total fluxes and there is no demand on biomass production. However, we will set a demand on the production of acetate and ethanol with a fixed value 1. |
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| 7. | lp = BuildLP.NoBiomassLP(m) lp.SetFixedFlux({'ACET_bp_tx': -1}) lp.SetFixedFlux({'ETOH_bp_tx': -1}) 8. Solve the LPEMs. We have written a small function that will solve the above lp and apply the LPEM algorithm on the solution and return you the LP solution (`sol`) and the LPEMS result (`modes`). sol, modes = lpems.GetLPEMs(m,lp) 9. Print the transport reactions active in the solution |
LPEMs ?
More constraint scaning ?
Link to the model archive here
LPEM algorithm decomposes the steady state flux vector into weighted elemetary modes such that the sum of these elementary modes is the original flux vector.
Here we will apply LPEM algorithm to genome scale metabolic model (GSM) of Acetobacter woodii. As seen in practical 4, the organism is capable of assimilating CO2, CO and H2 and produce acetate and ethanol. We will use the GSM of A. woodii to investigate the LPEMs utilized for the production of acetate and ethanol. We will see if the organism utilizes CO and H2.
Instructions
1. Download the required model and python code file from here. This is a zip file.
2. Copy the downloaded zip file in the workshop directory on your system and extract the zip file.
3. A new directory called P6 will be created. From the terminal, cd to the P6/model directory.
4. Start ScrumPy from this directory.
5. Read model. The name of the main model file is A.woodii.spy. Recall from previous practicals and read this model.
6. Add Analysis directory to path and import necessary modules
- import BuildLP
- import sys
- sys.path.append('../Analysis')
- import lpems
7. We will now create a LP problem from this model. We would make the LP such that its objective function is minimization of total fluxes and there is no demand on biomass production. However, we will set a demand on the production of acetate and ethanol with a fixed value 1.
- lp = BuildLP.NoBiomassLP(m)
lp.SetFixedFlux({'ACET_bp_tx': -1}) lp.SetFixedFlux({'ETOH_bp_tx': -1})
8. Solve the LPEMs. We have written a small function that will solve the above lp and apply the LPEM algorithm on the solution and return you the LP solution (sol) and the LPEMS result (modes).
- sol, modes = lpems.GetLPEMs(m,lp)
9. Print the transport reactions active in the solution