This module brings a Python interface to the tool StableMotifs (Jorge G. T. Zañudo and Réka Albert), for the control of Boolean networks.
The control predictions can be processed using the algorecell_types library, which eases the display and comparison with other control methods.
stablemotifs-python
is distributed as part of the CoLoMoTo docker.
conda install -c colomoto stablemotifs-python
pip install stablemotifs
python -m stablemotifs_setup
Documentation is available at https://stablemotifs-python.readthedocs.io.
Examples can be found at:
>>> import stablemotifs
Model loading:
>>> sm = stablemotifs.load("network.txt") # in BooleanNet format
# alternatively, load with biolqm in any format
>>> import biolqm
>>> lm = biolqm.load("model.zginml") # or any format support by bioLQM
>>> sm = stablemotifs.load(lm)
Reprogramming predictions:
>>> sr = sm.reprogramming_to_attractor({"A": 1, "B": 0})
>>> sr.as_table()
See help(sr)
for other display methods