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On Definition and Inference of Nonlinear Boolean Dynamic Networks
Univ Luxembourg, Luxembourg.
Univ Luxembourg, Luxembourg.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Univ Luxembourg, Luxembourg.
2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

Network reconstruction has become particularly important in systems biology, and is now expected to deliver information on causality. Systems in nature are inherently nonlinear. However, for nonlinear dynamical systems with hidden states, how to give a useful definition of dynamic networks is still an open question. This paper presents a useful definition of Boolean dynamic networks for a large class of nonlinear systems. Moreover, a robust inference method is provided. The well-known Millar-10 model in systems biology is used as a numerical example, which provides the ground truth of causal networks for key mRNAs involved in eukaryotic circadian clocks. In addition, as second contribution of this paper, we suggest definitions of linear network identifiability, which helps to unify the available work on network identifiability.

Place, publisher, year, edition, pages
IEEE , 2017.
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-145492DOI: 10.1109/CDC.2017.8263702ISI: 000424696900069ISBN: 978-1-5090-2873-3 (print)OAI: oai:DiVA.org:liu-145492DiVA, id: diva2:1187178
Conference
IEEE 56th Annual Conference on Decision and Control (CDC)
Note

Funding Agencies|Fonds National de la Recherche Luxembourg [AFR-9247977, AFR-8864515]

Available from: 2018-03-02 Created: 2018-03-02 Last updated: 2018-03-02

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf