Fixed point reprogramming with ActoNet

This notebook demonstrate usage of ActoNet to identify permanent control of Boolean network enforcing a given property We end with a validation using CABEAN

import actonet
import biolqm

lqm = biolqm.load("http://ginsim.org/sites/default/files/Bladder_Model.zginml")

Downloading http://ginsim.org/sites/default/files/Bladder_Model.zginml

inputs = {
    "GrowthInhibitors":1,
    "EGFR_stimulus":1,
    "FGFR3_stimulus":1
}
target = {"Apoptosis_b1": 1, "RB1": 1}

an = actonet.ActoNet(lqm, inputs)

s = an.reprogramming_fixpoints(target, maxsize=2)
s

[FromCondition('input', PermanentPerturbation(ATM_b1=1, p16INK4a=0)),
 FromCondition('input', PermanentPerturbation(DNAdamage=1, p16INK4a=0)),
 FromCondition('input', PermanentPerturbation(RB1=1, TP53=1)),
 FromCondition('input', PermanentPerturbation(Apoptosis_b1=1, RB1=1)),
 FromCondition('input', PermanentPerturbation(ATM_b1=1, RB1=1)),
 FromCondition('input', PermanentPerturbation(DNAdamage=1, RB1=1))]

s.as_graph()

s.aliases

	EGFR_stimulus	FGFR3_stimulus	GrowthInhibitors
input	1	1	1

s.as_table()

	ATM_b1	Apoptosis_b1	DNAdamage	RB1	TP53	p16INK4a
0				1	1
1			1			0
2			1	1
3		1		1
4	1					0
5	1			1

from colomoto.minibn import BooleanNetwork
from colomoto_jupyter import tabulate
import cabean # for attractor computation

test = biolqm.to_minibn(lqm, ensure_boolean=True)
for n, v in inputs.items():
    test[n] = v
test["RB1"] = 1
test["TP53"] = 1

import cabean

tabulate(cabean.attractors(test))

	AKT	ATM_b1	ATM_b2	Apoptosis_b1	Apoptosis_b2	CDC25A	CHEK1_2_b1	CHEK1_2_b2	CyclinA	CyclinD1	CyclinE1	DNAdamage	E2F1_b1	E2F1_b2	E2F3_b1	E2F3_b2	EGFR	EGFR_stimulus	FGFR3	FGFR3_stimulus	GRB2	GrowthInhibitors	Growth_Arrest	MDM2	PI3K	PTEN	Proliferation	RAS	RB1	RBL2	SPRY	TP53	p14ARF	p16INK4a	p21CIP
0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	1	1	0	0	1	0	1	1	1	1	1	0	0	1
1	0	1	0	1	0	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	0	1	1	0	0	1	0	1	1	1	1	1	0	0	1