Practical 6
Linear Programming and Flux Balance Analysis with ScrumPy
In this practical you will try to repeat the results from Fell & Small (1986), which was one of the first attempts to apply LP to metabolic networks. Before staring with the exercises read the documentation of the ScrumPy LP module, here.
- Download the original paper from this link. Download and open the adipose model (adipose.spy). Your task is to set up and solve an LP problem where the objective is to minimise glucose consumption, while producing 1 unit of triacylglycerol (TGA).
- Start by importing the LP module and create the LP object with the adipose model as argument. Set the flux of the TGA-synthesising reaction to 1.0, by entering this information to the appropriate LP method, i.e. we are going to optimise the production of one unit of triglyceride.
- Hint 1 Hint 2
- Hint
To obtain the solution use the LP method GetPrimSol(). This method returns a dictionary object of reactions in the solution as keys and flux values as values, so for convenience assign a name to this solution.
- Start by importing the LP module and create the LP object with the adipose model as argument. Set the flux of the TGA-synthesising reaction to 1.0, by entering this information to the appropriate LP method, i.e. we are going to optimise the production of one unit of triglyceride.