A SAT-Based Method for Counting All Singleton Attractors in Boolean Networks
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.
Cite
Text
Higuchi et al. "A SAT-Based Method for Counting All Singleton Attractors in Boolean Networks." International Joint Conference on Artificial Intelligence, 2025. doi:10.24963/IJCAI.2025/290Markdown
[Higuchi et al. "A SAT-Based Method for Counting All Singleton Attractors in Boolean Networks." International Joint Conference on Artificial Intelligence, 2025.](https://mlanthology.org/ijcai/2025/higuchi2025ijcai-sat/) doi:10.24963/IJCAI.2025/290BibTeX
@inproceedings{higuchi2025ijcai-sat,
title = {{A SAT-Based Method for Counting All Singleton Attractors in Boolean Networks}},
author = {Higuchi, Rei and Soh, Takehide and Le Berre, Daniel and Magnin, Morgan and Banbara, Mutsunori and Tamura, Naoyuki},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2025},
pages = {2601-2609},
doi = {10.24963/IJCAI.2025/290},
url = {https://mlanthology.org/ijcai/2025/higuchi2025ijcai-sat/}
}