In this notebook, we show how the computational of the fixpoints of qualitative regulatory networks can be done with different methods, which should give equivalent results, using GINsim and Pint.

Model loading

We load a simple model available on http://ginsim.org/node/41

In [1]:
import pandas as pd # for displaying list of fixpoints
import ginsim
In [2]:
th17 = ginsim.load("http://ginsim.org/sites/default/files/Th_17.zginml")

Downloading 'http://ginsim.org/sites/default/files/Th_17.zginml' to 'gen/colomotolgvlbbncTh_17.zginml'

Computation of fixpoints with bioLQM

In [3]:
import biolqm
In [4]:
th17_lqm = ginsim.to_biolqm(th17)
In [5]:
fps_lqm = biolqm.fixpoints(th17_lqm)
pd.DataFrame(fps_lqm)
Out[5]:
GATA3 IFNb IFNbR IFNg IFNgR IL12 IL12R IL18 IL18R IL4 IL4R IRAK SOCS1 STAT1 STAT4 STAT6 Tbet
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0
2 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 1
3 0 0 0 2 1 0 0 0 0 0 0 0 1 1 0 0 2

Computation of fixpoints with Pint

In [6]:
import pypint

You are using Pint version 2017-12-19 and pypint 1.3.94

In [7]:
th17_an = biolqm.to_pint(th17_lqm)

Source file is in Automata Network (an) format

In [8]:
fps_an = pypint.fixpoints(th17_an)
pd.DataFrame(fps_an)
Out[8]:
GATA3 IFNb IFNbR IFNg IFNgR IL12 IL12R IL18 IL18R IL4 IL4R IRAK SOCS1 STAT1 STAT4 STAT6 Tbet
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0
2 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 1
3 0 0 0 2 1 0 0 0 0 0 0 0 1 1 0 0 2

Display fixpoint using GINsim

In [9]:
ginsim.show(th17, fps_lqm[1]) # or fps_an[1]
Out[9]:
In [ ]: