Reference : Recent development and biomedical applications of probabilistic Boolean networks

	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/4561

Title :	Recent development and biomedical applications of probabilistic Boolean networks
Language :	English
Author, co-author :	Trairatphisan, Panuwat [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
	Mizera, Andrzej [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)]
	Tantar, Alexandru-Adrian [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Schneider, Jochen [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Sauter, Thomas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Publication date :	1-Jul-2013
Journal title :	Cell Communication and Signaling
Publisher :	BioMed Central
Volume :	11
Issue/season :	46
Special issue title :	Systems Biology and Medicine
Peer reviewed :	Yes
Audience :	International
e-ISSN :	1478-811X
Keywords :	[en] probabilistic Boolean networks ; Probabilistic graphical models ; Qualitative modelling ; Systems biology
Abstract :	[en] Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based representation and probability makes PBN appealing for large-scale modelling of biological networks where degrees of uncertainty need to be considered. A considerable expansion of our knowledge in the field of theoretical research on PBN can be observed over the past few years, with a focus on network inference, network intervention and control. With respect to areas of applications, PBN is mainly used for the study of gene regulatory networks though with an increasing emergence in signal transduction, metabolic, and also physiological networks. At the same time, a number of computational tools, facilitating the modelling and analysis of PBNs, are continuously developed. A concise yet comprehensive review of the state-of-the-art on PBN modelling is offered in this article, including a comparative discussion on PBN versus similar models with respect to concepts and biomedical applications. Due to their many advantages, we consider PBN to stand as a suitable modelling framework for the description and analysis of complex biological systems, ranging from molecular to physiological levels.
Research centres :	Life Sciences Research Unit
Funders :	Fonds National de la Recherche - FnR
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/4561
DOI :	10.1186/1478-811X-11-46
Other URL :	http://www.biosignaling.com/content/11/1/46

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	Fulltext file(s): File Commentary Version Size Access Open access [Formatted_Full_Text]1478-811X-11-46.pdf Provisional manuscript (published 1st July 2013), full text will be available and updated later Publisher postprint 1 MB View/Open

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