PyBoolNet tutorial

PyBoolNet tutorial#

Boolean networks#

from pyboolnet.file_exchange import bnet2primes, primes2bnet
from pyboolnet.prime_implicants import find_constants, create_variables
from pyboolnet.repository import get_primes

# Manual model definition
bnet = """
v1,	!v1
v2,	1
v3,	v2 & (!v1 | v3)
"""

primes = bnet2primes(bnet)

# finding nodes
find_constants(primes)

{'v2': 1}

# modifying networks
create_variables(primes, {"v4": "v4 | v2"})
create_variables(primes, {"v5": lambda v1,v2,v3: v1+v2+v3==1})

print(primes2bnet(primes))

v2,   

v1,   !v1
v3,   v2 & v3 | !v1 & v2
v4,   v4 | v2

v5,   !v1 & !v2 & v3 | !v1 & v2 & !v3 | v1 & !v2 & !v3

From repository#

See hklarner/pyboolnet

# reading from the repository
primes = get_primes("remy_tumorigenesis")
print(primes2bnet(primes))

DNA_damage,          DNA_damage
EGFR_stimulus,       EGFR_stimulus
FGFR3_stimulus,      FGFR3_stimulus
Growth_inhibitors,   Growth_inhibitors

AKT,                 PI3K
ATM_high,            ATM_medium & DNA_damage & E2F1_medium
ATM_medium,          ATM_high & ATM_medium | DNA_damage
Apoptosis_high,      Apoptosis_medium & E2F1_high & E2F1_medium
Apoptosis_medium,    E2F1_high & E2F1_medium | Apoptosis_high & Apoptosis_medium | TP53
CDC25A,              !CHEK1_2_medium & E2F3_medium & !RBL2 | !CHEK1_2_medium & E2F1_medium & !RBL2
CHEK1_2_high,        ATM_medium & CHEK1_2_medium & E2F1_medium
CHEK1_2_medium,      CHEK1_2_high & CHEK1_2_medium | ATM_medium
CyclinA,             CDC25A & E2F3_medium & !RBL2 & !p21CIP | CDC25A & E2F1_medium & !RBL2 & !p21CIP
CyclinD1,            RAS & !p16INK4a & !p21CIP | AKT & !p16INK4a & !p21CIP
CyclinE1,            CDC25A & E2F3_medium & !RBL2 & !p21CIP | CDC25A & E2F1_medium & !RBL2 & !p21CIP
E2F1_high,           ATM_high & ATM_medium & CHEK1_2_high & CHEK1_2_medium & E2F1_medium & E2F3_high & E2F3_medium & !RB1 & !RBL2 | ATM_high & ATM_medium & CHEK1_2_high & CHEK1_2_medium & E2F1_medium & RAS & !RB1 & !RBL2
E2F1_medium,         RAS & !RB1 & !RBL2 | E2F3_medium & !RB1 & !RBL2 | E2F1_high & E2F1_medium
E2F3_high,           CHEK1_2_high & CHEK1_2_medium & E2F3_medium & RAS & !RB1
E2F3_medium,         RAS & !RB1 | E2F3_high & E2F3_medium
EGFR,                !FGFR3 & !GRB2 & SPRY | EGFR_stimulus & !FGFR3 & !GRB2
FGFR3,               !EGFR & FGFR3_stimulus & !GRB2
GRB2,                FGFR3 & !GRB2 & !SPRY | EGFR
MDM2,                !ATM_medium & !RB1 & TP53 & !p14ARF | AKT & !ATM_medium & !RB1 & !p14ARF
PI3K,                GRB2 & !PTEN & RAS
PTEN,                TP53
RAS,                 GRB2 | FGFR3 | EGFR
RB1,                 !CyclinA & !CyclinD1 & !CyclinE1 & !p16INK4a
RBL2,                !CyclinD1 & !CyclinE1
SPRY,                RAS
TP53,                E2F1_high & E2F1_medium & !MDM2 | ATM_medium & CHEK1_2_medium & !MDM2
p14ARF,              E2F1_medium
p16INK4a,            Growth_inhibitors & !RB1
p21CIP,              !AKT & !CyclinE1 & TP53 | !AKT & !CyclinE1 & Growth_inhibitors

Growth_arrest,       p21CIP | RBL2 | RB1
Proliferation,       CyclinE1 | CyclinA

Trap spaces#

from pyboolnet.trap_spaces import compute_trap_spaces, compute_steady_states

from colomoto_jupyter import tabulate

This notebook has been executed using the docker image colomoto/colomoto-docker:2021-10-01

mints = compute_trap_spaces(primes, "min")
tabulate(mints)
p21CIP p16INK4a p14ARF TP53 SPRY RBL2 RB1 RAS Proliferation PTEN PI3K MDM2 Growth_inhibitors Growth_arrest GRB2 FGFR3_stimulus FGFR3 EGFR_stimulus EGFR E2F3_medium E2F3_high E2F1_medium E2F1_high DNA_damage CyclinE1 CyclinD1 CyclinA CHEK1_2_medium CHEK1_2_high CDC25A Apoptosis_medium Apoptosis_high ATM_medium ATM_high AKT
0 0.0 0 0.0 0 0.0 1.0 1.0 0.0 0.0 0 0.0 0.0 0 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
18 0.0 0 1.0 0 1.0 0.0 0.0 1.0 1.0 0 0.0 0.0 0 0.0 0.0 1 1 0 0.0 1.0 0 1.0 0 0 1.0 1.0 1.0 0 0 1.0 0 0 0 0 0.0
17 0.0 0 1.0 0 1.0 0.0 0.0 1.0 1.0 0 0.0 0.0 0 0.0 0.0 1 1 1 0.0 1.0 0 1.0 0 0 1.0 1.0 1.0 0 0 1.0 0 0 0 0 0.0
24 0.0 0 NaN 0 NaN NaN NaN NaN NaN 0 NaN NaN 0 NaN NaN 0 0 1 NaN NaN 0 NaN 0 0 NaN NaN NaN 0 0 NaN 0 0 0 0 NaN
8 0.0 1 1.0 0 1.0 0.0 0.0 1.0 1.0 0 0.0 0.0 1 0.0 0.0 1 1 0 0.0 1.0 0 1.0 0 0 1.0 0.0 1.0 0 0 1.0 0 0 0 0 0.0
7 0.0 1 1.0 0 1.0 0.0 0.0 1.0 1.0 0 0.0 0.0 1 0.0 0.0 1 1 1 0.0 1.0 0 1.0 0 0 1.0 0.0 1.0 0 0 1.0 0 0 0 0 0.0
2 1.0 0 0.0 0 0.0 1.0 1.0 0.0 0.0 0 0.0 0.0 1 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
23 1.0 0 0.0 0 1.0 1.0 1.0 1.0 0.0 0 0.0 0.0 1 1.0 0.0 1 1 0 0.0 0.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
4 1.0 0 0.0 0 1.0 1.0 1.0 1.0 0.0 0 0.0 0.0 1 1.0 0.0 1 1 1 0.0 0.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
3 1.0 0 0.0 1 0.0 1.0 1.0 0.0 0.0 1 0.0 0.0 0 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
1 1.0 0 0.0 1 0.0 1.0 1.0 0.0 0.0 1 0.0 0.0 1 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
20 1.0 0 0.0 1 1.0 1.0 1.0 1.0 0.0 1 0.0 0.0 0 1.0 0.0 1 1 0 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
5 1.0 0 0.0 1 1.0 1.0 1.0 1.0 0.0 1 0.0 0.0 0 1.0 0.0 1 1 1 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
22 1.0 0 0.0 1 1.0 1.0 1.0 1.0 0.0 1 0.0 0.0 1 1.0 0.0 1 1 0 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
6 1.0 0 0.0 1 1.0 1.0 1.0 1.0 0.0 1 0.0 0.0 1 1.0 0.0 1 1 1 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
19 1.0 0 0.0 1 NaN 1.0 1.0 NaN 0.0 1 0.0 0.0 0 1.0 NaN 0 0 1 NaN 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
21 1.0 0 0.0 1 NaN 1.0 1.0 NaN 0.0 1 0.0 0.0 1 1.0 NaN 0 0 1 NaN 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
13 1.0 1 0.0 0 0.0 1.0 0.0 0.0 0.0 0 0.0 0.0 1 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
16 1.0 1 0.0 0 1.0 1.0 0.0 1.0 0.0 0 0.0 0.0 1 1.0 0.0 1 1 0 0.0 1.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
15 1.0 1 0.0 0 1.0 1.0 0.0 1.0 0.0 0 0.0 0.0 1 1.0 0.0 1 1 1 0.0 1.0 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 0.0
9 1.0 1 0.0 1 0.0 1.0 0.0 0.0 0.0 1 0.0 0.0 1 1.0 0.0 0 0 0 0.0 0.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
12 1.0 1 0.0 1 1.0 1.0 0.0 1.0 0.0 1 0.0 0.0 1 1.0 0.0 1 1 0 0.0 1.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
11 1.0 1 0.0 1 1.0 1.0 0.0 1.0 0.0 1 0.0 0.0 1 1.0 0.0 1 1 1 0.0 1.0 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
10 1.0 1 0.0 1 NaN 1.0 0.0 NaN 0.0 1 0.0 0.0 1 1.0 NaN 0 0 1 NaN NaN 0 0.0 0 1 0.0 0.0 0.0 1 0 0.0 1 0 1 0 0.0
14 NaN 1 0.0 0 NaN 1.0 0.0 NaN 0.0 0 NaN NaN 1 1.0 NaN 0 0 1 NaN NaN 0 0.0 0 0 0.0 0.0 0.0 0 0 0.0 0 0 0 0 NaN 
max_trap_spaces = compute_trap_spaces(primes, "max")
tabulate(max_trap_spaces)
EGFR_stimulus Growth_inhibitors FGFR3_stimulus DNA_damage
5 0.0 NaN NaN NaN
0 1.0 NaN NaN NaN
2 NaN 0.0 NaN NaN
1 NaN 1.0 NaN NaN
4 NaN NaN 0.0 NaN
3 NaN NaN 1.0 NaN
7 NaN NaN NaN 0.0
6 NaN NaN NaN 1.0 
steady = compute_steady_states(primes)
tabulate(steady)
p21CIP p16INK4a p14ARF TP53 SPRY RBL2 RB1 RAS Proliferation PTEN PI3K MDM2 Growth_inhibitors Growth_arrest GRB2 FGFR3_stimulus FGFR3 EGFR_stimulus EGFR E2F3_medium E2F3_high E2F1_medium E2F1_high DNA_damage CyclinE1 CyclinD1 CyclinA CHEK1_2_medium CHEK1_2_high CDC25A Apoptosis_medium Apoptosis_high ATM_medium ATM_high AKT
0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
19 0 0 1 0 1 0 0 1 1 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 1 1 1 0 0 1 0 0 0 0 0
18 0 0 1 0 1 0 0 1 1 0 0 0 0 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 0 0 0 0
10 0 1 1 0 1 0 0 1 1 0 0 0 1 0 0 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0
8 0 1 1 0 1 0 0 1 1 0 0 0 1 0 0 1 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0
1 1 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
17 1 0 0 0 1 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
16 1 0 0 0 1 1 1 1 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
3 1 0 0 1 0 1 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
2 1 0 0 1 0 1 1 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
13 1 0 0 1 1 1 1 1 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
12 1 0 0 1 1 1 1 1 0 1 0 0 0 1 0 1 1 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
15 1 0 0 1 1 1 1 1 0 1 0 0 1 1 0 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
14 1 0 0 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
5 1 1 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
11 1 1 0 0 1 1 0 1 0 0 0 0 1 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
9 1 1 0 0 1 1 0 1 0 0 0 0 1 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
4 1 1 0 1 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
7 1 1 0 1 1 1 0 1 0 1 0 0 1 1 0 1 1 0 0 1 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0
6 1 1 0 1 1 1 0 1 0 1 0 0 1 1 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0