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