Taming Asynchrony for Attractor Detection in Large Boolean Networks (Technical Report)
Molecular Networks
2017-06-14 v3 Distributed, Parallel, and Cluster Computing
Quantitative Methods
Abstract
Boolean networks is a well-established formalism for modelling biological systems. A vital challenge for analysing a Boolean network is to identify all the attractors. This becomes more challenging for large asynchronous Boolean networks, due to the asynchronous updating scheme. Existing methods are prohibited due to the well-known state-space explosion problem in large Boolean networks. In this paper, we tackle this challenge by proposing a SCC-based decomposition method. We prove the correctness of our proposed method and demonstrate its efficiency with two real-life biological networks.
Cite
@article{arxiv.1704.06530,
title = {Taming Asynchrony for Attractor Detection in Large Boolean Networks (Technical Report)},
author = {Andrzej Mizera and Jun Pang and Hongyang Qu and Qixia Yuan},
journal= {arXiv preprint arXiv:1704.06530},
year = {2017}
}
Comments
28 pages, version 3 (correct a mistake in Table 2)