Reference : Recent development and biomedical applications of probabilistic Boolean networks
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/4561
Recent development and biomedical applications of probabilistic Boolean networks
English
Trairatphisan, Panuwat mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Mizera, Andrzej mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Pang, Jun mailto [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 mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Schneider, Jochen mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
1-Jul-2013
Cell Communication and Signaling
BioMed Central
11
46
Systems Biology and Medicine
Yes
International
1478-811X
[en] probabilistic Boolean networks ; Probabilistic graphical models ; Qualitative modelling ; Systems biology
[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.
Life Sciences Research Unit
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/4561
10.1186/1478-811X-11-46
http://www.biosignaling.com/content/11/1/46

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