optimalRays

findExtremePathway(fbaModel, obj)

Finds an extreme ray

USAGE:

[x, output] = findExtremePathway(fbaModel, obj)

INPUT:

fbaModel: FBA type model

OPTIONAL INPUT:

obj: default = random vector with size depending on fbaModel.S

OUTPUTS:

x: vector from result, where result is an output of solveCobraLP function output: output.objval contains result.obj

findExtremePool(fbaModel, obj, printLevel)

Finds an extreme ray in the left nullspace of the stoichiometric matrix

USAGE:

[x, output] = findExtremePool(fbaModel, obj, printLevel)

INPUT:

fbaModel: FBA type model

OPTIONAL INPUT:

obj: default = random vector with size depending on fbaModel.S printLevel: argument for solveCobraLP function, default = 0

OUTPUTS:

x: x = output.full output: output = solveCobraLP(LPProblem)

greedyExtremePoolBasis(model)

Computes a non-negative basis for the left nullspace of the stoichiometric matrix using optimization to pick random extreme rays, then test a posteriori if each is linearly independent from the existing stored extreme rays.

USAGE:

[B, L] = greedyExtremePoolBasis(model)

INPUT:

model: model structure

OUTPUTS:

B, L: non-negative basus fi the left nullspace

optimalExtremePoolDriver

Script to test extremePathways.m