Paper Info
Title
Synthesis of Boolean Networks from Biological Dynamical Constraints using Answer-Set Programming
Abstract
Boolean networks model finite discrete dynamical systems with complex behaviours. The state of each component is determined by a Boolean function of the state of (a subset of) the components of the network. This paper addresses the synthesis of these Boolean functions from constraints on their domain and emerging dynamical properties of the resulting network. The dynamical properties relate to the existence and absence of trajectories between partially observed configurations, and to the stable behaviours (fixpoints and cyclic attractors). The synthesis is expressed as a Boolean satisfiability problem relying on Answer-Set Programming with a parametrized complexity, and leads to a complete non-redundant characterization of the set of solutions. Considered constraints are particularly suited to address the synthesis of models of cellular differentiation processes, as illustrated on a case study. The scalability of the approach is demonstrated on random networks with scale-free structures up to 100 to 1,000 nodes depending on the type of constraints.
Year
DOI
Venue
2019
10.1109/ICTAI.2019.00014
2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)
Keywords
Field
DocType
model synthesis,discrete dynamical systems,reachability,attractors,systems biology
Boolean function,Attractor,Computer science,Boolean satisfiability problem,Systems biology,Theoretical computer science,Reachability,Dynamical systems theory,Artificial intelligence,Answer set programming,Machine learning,Scalability
Conference
ISSN
ISBN
Citations 
1082-3409
978-1-7281-3799-5
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Stéphanie Chevalier100.34
Christine Froidevaux200.34
Loïc Paulevé320418.68
Andrei Zinovyev428227.30