Welcome to mpbn’s documentation!

This module provides a simple implementation of Most Permissive Boolean Networks (MPBNs) for computing reachability properties, attractors, and reachable attractors in locally-monotonic Boolean networks. See http://dx.doi.org/10.1101/2020.03.22.998377 and https://arxiv.org/abs/1808.10240 for technical details.

It relies on clingo Answer-Set Programming solver (https://github.com/potassco/clingo).

Examples are available at https://nbviewer.jupyter.org/github/pauleve/mpbn/tree/master/examples/

Quick example:

>>> mbn = mpbn.MPBooleanNetwork({
        "a": "!b",
        "b": "!a",
        "c": "!a & b"})
>>> list(mbn.attractors())
[{'a': 0, 'b': 1, 'c': 1}, {'a': 1, 'b': 0, 'c': 0}]
>>> mbn.reachability({'a': 0, 'b': 1, 'c': 1}, {'a': 1, 'b': 0, 'c': 0})
False
>>> mbn.reachability({'a': 0, 'b': 0, 'c': 0}, {'a': 1, 'b': 1, 'c': 1})
True
>>> list(mbn.attractors(reachable_from={'a': 0, 'b': 1, 'c': 0}))
[{'a': 0, 'b': 1, 'c': 1}]
mpbn.load(filename, **opts)[source]

Create a MPBooleanNetwork object from filename in BoolNet format; filename can be a local file or an URL.

class mpbn.MPBooleanNetwork(bn={}, auto_dnf=True)[source]

Most Permissive Boolean Network

Extends colomoto.minibn.BooleanNetwork class by adding methods for computing reachable and attractor properties with the Most Permissive semantics. It requires that the Boolean network is locally monotonic.

Ensures that the Boolean functions are monotonic and in disjunctive normal form (DNF). The local-monotonic checking requires that a literal never appears with both signs in a same Boolean function.

Constructor for MPBoooleanNetwork.

Parameters:
  • bn (colomoto.minibn.BooleanNetwork or any type accepted by colomoto.minibn.BooleanNetwork constructor) – Boolean network to copy from
  • auto_dnf (bool) – if False, turns off automatic DNF transformation of local functions

Examples:

>>> mbn = MPBooleanNetwork("network.bnet")
>>> bn = BooleanNetwork()
>>> bn["a"] = ".."; ...
>>> mbn = MPBooleanNetwork(bn)
attractors(reachable_from=None, constraints={}, limit=0, star='*')[source]

Iterator over attractors of the MPBN. An attractor is an hypercube, represented by a dictionnary mapping every component of the network to either 0, 1, or star.

Parameters:
  • reachable_from (dict[str,int]) – restrict to the attractors reachable from the given configuration. Whenever partial, restrict attractors to the one reachable by at least one matching configuration.
  • constraints (dict[str,int]) – consider only attractors matching with the given constraints.
  • limit (int) – maximum number of solutions, 0 for unlimited.
  • star (str) – value to use for components which are free in the attractor
reachability(x, y)[source]

Returns True whenever the configuration y is reachable from x with the Most Permissive semantics. Configurations can be partially defined. In that case, returns True whenever there exists a configuration matching with y which is reachable with at least one configuration matching with x

Parameters:
  • x (dict[str,int]) – initial configuration
  • y (dict[str,int]) – target configuration

Indices and tables