def essential_prot():
model = GeckoModel("single-pool")
model.solver = 'cplex'
print("Essential proteins with cplex, normal model (single-pool)")
for p in model.proteins:
with model as m:
r = m.reactions.get_by_id("draw_prot_" + p)
r.lower_bound = 0
r.upper_bound = 0
res = m.optimize()
if (res.objective_value <= 1e-10):
print(p, ",", res.objective_value)
def essential_prot_scale():
model = GeckoModel("single-pool")
model.solver = 'cplex'
print("Essential proteins with cplex, scale model (single-pool)")
for r in model.reactions:
r.lower_bound = r.lower_bound * 100000
r.upper_bound = r.upper_bound * 100000
for p in model.proteins:
with model as m:
r = model.reactions.get_by_id("draw_prot_" + p)
r.lower_bound = 0
r.upper_bound = 0
res = model.optimize()
print(p, ",", res.objective_value)
def simulate_prot():
model = GeckoModel("single-pool")
model.solver = 'cplex'
with model:
# for p in ["P53685","Q01574"]:
for p in ['P33421']:
r = model.reactions.get_by_id("draw_prot_" + p)
r.lower_bound = 0
r.upper_bound = 0
res = model.optimize()
print(" --> growth " + str(res.objective_value))
print(" --> r_2111 " + str(res.fluxes["r_2111"]))
print(" --> r_2056 " + str(res.fluxes["r_2056"]))
print(" --> r_1714 " + str(res.fluxes["r_1714_REV"]))
print(" ------------ ")
def analysis_growth(resFileName, scale=False):
model = GeckoModel('single-pool')
model.solver = 'cplex'
#scale model
if scale:
for r in model.reactions:
r.upper_bound = r.upper_bound * 100000
r.lower_bound = r.lower_bound * 100000
proteins = model.proteins
df = pandas.DataFrame(index=proteins, columns=range(100))
for i in range(100):
print(i)
for p in proteins:
with model as m:
r = m.reactions.get_by_id("draw_prot_" + p)
r.lower_bound = 0
r.upper_bound = 0
res = m.optimize()
df.loc[p][i] = 0 if res.objective_value < 1e-4 else 1
df.to_csv(resFileName)