A SAT-based Method for Counting All Singleton Attractors in Boolean Networks
Rei Higuchi, Takehide Soh, Daniel Le Berre, Morgan Magnin, Mutsunori Banbara, Naoyuki Tamura
Abstract
Boolean networks (BNs) are widely used to model biological regulatory networks. Attractors here hold significant meaning as they represent long-term behaviors such as homeostasis and the results of cell differentiation. As such, computing attractors is of critical importance to guarantee the validity of a model or to assess its stability and robustness. However, this problem is quite challenging when it comes to large real-world models. To overcome the limits of state-of-the-art BDD-based or ASP-based enumeration approaches, we introduce a SAT-based approach to compute fixed points (singleton attractors) of BN and exhibit its merits for counting the number of singleton attractors of large-scale benchmarks well established in the literature.
BibTeX
@inproceedings{ijcai2025_asatbasedmethodf,
title = {A SAT-based Method for Counting All Singleton Attractors in Boolean Networks},
author = {Rei Higuchi and Takehide Soh and Daniel Le Berre and Morgan Magnin and Mutsunori Banbara and Naoyuki Tamura},
booktitle = {IJCAI 2025},
year = {2025}
}