Taming Asynchrony for Attractor Detection in Large Boolean Networks

Andrzej Mizera, Jun Pang, Hongyang Qu, Qixia Yuan*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

21 Citations (Scopus)

Abstract

Boolean networks is a well-established formalism for modelling biological systems. A vital challenge for analyzing a Boolean network is to identify all the attractors. This becomes more challenging for large asynchronous Boolean networks, due to the asynchronous 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.

Original languageEnglish
Article number8398459
Pages (from-to)31-42
Number of pages12
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Asynchronous Boolean networks
  • attractor detection
  • binary decision diagram
  • gene regulatory networks
  • strongly connected components

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