def SMILEY(model, metabolite_id, Universal=None):
"""
runs the SMILEY algorithm to determine which gaps should be
filled in order for the model to create the metabolite with the
given metabolite_id.
This function is good for running the algorithm once. For more fine-
grained control, create a SUXModelMILP object, add a demand reaction
for the given metabolite_id, and call the solve function on the
SUXModelMILP object.
"""
if Universal is None:
Universal = import_kegg_reactions()
SUX = SUXModelMILP(model, Universal)
# change the objective to be the metabolite
for reaction in SUX.original_reactions:
reaction.objective_coefficient = 0
demand_reaction = cobra.Reaction("SMILEY_DEMAND_RXN_%s" % metabolite_id)
demand_reaction.objective_coefficient = 1
demand_reaction.add_metabolites(
{SUX.metabolites[SUX.metabolites.index(metabolite_id)]: -1})
SUX.add_reaction(demand_reaction)
used_reactions = SUX.solve()
for reaction in used_reactions:
print reaction, SUX.solution.x_dict[reaction.id]
return used_reactions
def growMatch(model, Universal=None):
"""runs growMatch"""
if Universal is None:
Universal = import_kegg_reactions()
SUX = SUXModelMILP(model, Universal)
used_reactions = SUX.solve()
for reaction in used_reactions:
print reaction, SUX.solution.x_dict[reaction.id]
return used_reactions
print reaction, SUX.solution.x_dict[reaction.id]
return used_reactions
if __name__ == "__main__":
from cPickle import load
from os.path import join, abspath, dirname
from time import time
import cobra
test_file_path = join(dirname(cobra.__file__), "test", "data", \
"salmonella.pickle")
test_file = open(test_file_path, "rb")
model = load(test_file)
test_file.close()
tic = time()
Universal = import_kegg_reactions()
toc = time()
print "%.2f sec to import kegg reactions" % (toc - tic)
tic = toc
print "growMatch: "
growMatch(model, Universal)
toc = time()
print "%.2f sec for growmatch" % (toc - tic)
tic = toc
print "SMILEY results"
SMILEY(model, "atp_c", Universal)
toc = time()
print "%.2f sec for smiley" % (toc - tic)
