= Introduction to LPEMs =
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 [[https://mudshark.brookes.ac.uk/Meetings/Nottingham2024/Prac4|practical 4]], the organism is capable of  assimilating CO,,2,,, CO and H,,2 ,,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  H,,2,,.

'''Instructions'''

1. Download the required model and python code file from [[http://mudsharkstatic.brookes.ac.uk/Nottingham2024/P6.zip|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/Analysis `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. Read Model

{{{#!python
 m = ScrumPy.Model('../model/A.woodii.spy')
}}}
7. Import the BuildLP module that will help us create LP problem.

{{{#!python
import BuildLP
}}}
8. 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.

{{{#!python
lp = BuildLP.NoBiomassLP(m)
lp.SetFixedFlux({'ACET_bp_tx': -1})
lp.SetFixedFlux({'ETOH_bp_tx': -1})
}}}
9. We will solve this LP problem and calculate the LPEMs for the solution. 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`).

{{{#!python
import lpems
sol, modes = lpems.GetLPEMs(m,lp)
}}}
10. Print the transport reactions active in the solution. Hint: The transport reaction ids have `_tx` in them.

11. How many reaction are active in the solution?

12. How many LPEM modes did you get?

To print the modes use following command

{{{#!python
print(modes.Stos())
}}}