Recent development and biomedical applications of probabilistic Boolean networks

Cell Communication and Signaling

Review

Andrzej Mizera¹  Jun Pang¹  Alexandru Adrian Tantar²  Thomas Sauter³  Panuwat Trairatphisan³  Jochen Schneider⁴ 

[1] Computer Science and Communications Research Unit, University of Luxembourg, Luxembourg;Computer Science and Communications Research Unit, University of Luxembourg, Luxembourg;Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg;Life Sciences Research Unit, University of Luxembourg, Luxembourg;Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg;Department of Internal Medicine II, Saarland University Medical Center, Homburg, Saarland, Germany;

关键词: Probabilistic Boolean networks;    Probabilistic graphical models;    Qualitative modelling;    Systems biology;   

DOI  :  10.1186/1478-811X-11-46

 received in 2013-03-29, accepted in 2013-06-22,  发布年份 2013

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© Trairatphisan et al.; licensee BioMed Central Ltd. 2013