Reference : Improving BDD-based attractor detection for synchronous Boolean networks

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/25937

Title :	Improving BDD-based attractor detection for synchronous Boolean networks
Language :	English
Author, co-author :	Qu, Hongyang [University of Sheffield]
	Yuan, Qixia [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Pang, Jun [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
	Mizera, Andrzej [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	2015
Main document title :	Proceedings of the 7th Asia-Pacific Symposium on Internetware
Publisher :	ACM
Peer reviewed :	Yes
Audience :	International
Event name :	7th Asia-Pacific Symposium on Internetware
Event date :	06-11-2015
Keywords :	[en] Boolean networks ; systems biology ; binary decision diagram
Abstract :	[en] Boolean networks are an important formalism for modelling biological systems and have attracted much attention in recent years. An important direction in Boolean networks is to exhaustively find attractors, which represent steady states when a biological network evolves for a long term. In this paper, we propose a new approach to improve the efficiency of BDD-based attractor detection. Our approach includes a monolithic algorithm for small networks, an enumerative strategy to deal with large networks, and two heuristics on ordering BDD variables. We demonstrate the performance of our approach on a number of examples, and compare it with one existing technique in the literature.
Permalink :	http://hdl.handle.net/10993/25937
FnR project :	FnR ; FNR7814267 > Qixia Yuan > > New Approaches to Parameter Estimation of Gene Regulatory Networks > 01/03/2014 > 14/01/2017 > 2014

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