Taming Asynchrony for Attractor Detection in Large Boolean Networks (Technical Report)

April 20, 2017 Β· Declared Dead Β· πŸ› IEEE/ACM Transactions on Computational Biology & Bioinformatics

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Authors Andrzej Mizera, Jun Pang, Hongyang Qu, Qixia Yuan arXiv ID 1704.06530 Category q-bio.MN Cross-listed cs.DC, q-bio.QM Citations 37 Venue IEEE/ACM Transactions on Computational Biology & Bioinformatics Last Checked 3 months ago
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.
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