import biolqm
import cabean
from colomoto_jupyter import tabulate
<IPython.core.display.Markdown object>
Myeolid reprogramming with CABEAN#
Import the myeloid network (Krumsiek et al. doi: 10.1371/journal.pone.0022649)
model = biolqm.load("MyeloidRules.txt", "booleannet")
Use the decompositon-based attractor detection method to identify all the exact attractors of the network.
%time attractors = cabean.attractors(model)
tabulate(attractors)
CPU times: user 5.7 ms, sys: 9.01 ms, total: 14.7 ms
Wall time: 52.2 ms
| CEBPA | EKLF | EgrNab | FOG1 | Fli1 | GATA1 | GATA2 | Gfi1 | PU1 | SCL | cJun | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 |
| 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
| 3 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 |
| 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 |
| 5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
Define the properties of the source and target attractors. Note that source or target may correspond to serveral attractors.
source = {"EgrNab": 0, "CEBPA": 1}
target = {"EgrNab": 1, "CEBPA": 1}
Compute the minimal one-step instantaneous control (OI) from the source to the target.
c1i = cabean.OneStep_Instantaneous(model)
s1i = c1i.attractor_to_attractor(source, target)
s1i
[FromSteadyState('a4', InstantaneousPerturbation(EgrNab=1, Gfi1=0, cJun=1))]
s1i.as_table()
| EgrNab | Gfi1 | cJun | |
|---|---|---|---|
| 0 | 1 | 0 | 1 |
Compute the attractor-based sequential instantaneous control (ASI) from the source to the target.
ci = cabean.AttractorSequential_Instantaneous(model)
si = ci.attractor_to_attractor(source, target)
si
[FromSteadyState('a4', InstantaneousPerturbation(EgrNab=1, Gfi1=0, cJun=1)),
FromSteadyState('a4', InstantaneousPerturbation(CEBPA=0),
FromSteadyState('a2', InstantaneousPerturbation(CEBPA=1)))]
si.as_graph()
si.as_table()
| CEBPA | EgrNab | Gfi1 | cJun | |
|---|---|---|---|---|
| 0 | 1 | 0 | 1 | |
| 1 | * |
Compute the minimal one-step temporary control (OT) from the source to the target.
c1t = cabean.OneStep_Temporary(model)
s1t = c1t.attractor_to_attractor(source, target)
s1t
[FromSteadyState('a4', TemporaryPerturbation(Gfi1=0)),
FromSteadyState('a4', TemporaryPerturbation(EgrNab=1))]
s1t.as_table()
| EgrNab | Gfi1 | |
|---|---|---|
| 0 | 0 | |
| 1 | 1 |
Compute the attractor-based sequential temporary control (AST) from the source to the target.
ct = cabean.AttractorSequential_Temporary(model)
st = ct.attractor_to_attractor(source, target)
st
[FromSteadyState('a4', TemporaryPerturbation(Gfi1=0)),
FromSteadyState('a4', TemporaryPerturbation(EgrNab=1))]
st.as_table()
| EgrNab | Gfi1 | |
|---|---|---|
| 0 | 0 | |
| 1 | 1 |
Compute the minimal one-step permanent control (OP) from the source to the target.
c1p = cabean.OneStep_Permanent(model)
s1p = c1p.attractor_to_attractor(source, target)
s1p
[FromSteadyState('a4', PermanentPerturbation(Gfi1=0)),
FromSteadyState('a4', PermanentPerturbation(EgrNab=1))]
s1p.as_table()
| EgrNab | Gfi1 | |
|---|---|---|
| 0 | 0 | |
| 1 | 1 |
Compute the attractor-based sequential permanent control (ASP) from the source to the target.
rp = cabean.AttractorSequential_Permanent(model)
%time sp = rp.attractor_to_attractor(source, target)
sp
CPU times: user 2.58 ms, sys: 5.43 ms, total: 8.01 ms
Wall time: 56.7 ms
[FromSteadyState('a4', PermanentPerturbation(Gfi1=0)),
FromSteadyState('a4', PermanentPerturbation(EgrNab=1))]
sp.as_graph()
sp.as_table()
| EgrNab | Gfi1 | |
|---|---|---|
| 0 | 0 | |
| 1 | 1 |