Reference : Reviving the two-state Markov chain approach
Scientific journals : Article
Life sciences : Biotechnology
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/34366
Reviving the two-state Markov chain approach
English
Mizera, Andrzej mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
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)]
Yuan, Qixia mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2018
IEEE/ACM Transactions on Computational Biology and Bioinformatics
IEEE Computer Society
Yes (verified by ORBilu)
International
1545-5963
1557-9964
New-York
NY
[en] Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such systems. However, for large PBNs, which often arise in systems biology, obtaining the steady-state distribution poses a significant challenge. In this paper, we revive the two-state Markov chain approach to solve this problem. This paper contributes in three aspects. First, we identify a problem of generating biased results with the approach and we propose a few heuristics to avoid such a pitfall. Secondly, we conduct an extensive experimental comparison of the extended two-state Markov chain approach and another approach based on the Skart method. We analyse the results with machine learning techniques and we show that statistically the two-state Markov chain approach has a better performance. Finally, we demonstrate the potential of the extended two-state Markov chain approach on a case study of a large PBN model of apoptosis in hepatocytes.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/34366

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