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On definition and inference of nonlinear Boolean dynamic networks
Yue, Zuogong; Thunberg, Johan; Ljung, Lennart et al.
2017In On definition and inference of nonlinear Boolean dynamic networks
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Keywords :
system identification; network inference; systems biology
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.
Research center :
- Luxembourg Centre for Systems Biomedicine (LCSB): Systems Control (Goncalves Group)
Disciplines :
Electrical & electronics engineering
Author, co-author :
Yue, Zuogong ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Life Science Research Unit
Thunberg, Johan ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Ljung, Lennart
Goncalves, Jorge ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
yes
Language :
English
Title :
On definition and inference of nonlinear Boolean dynamic networks
Publication date :
December 2017
Event name :
56th IEEE Conference on Decision and Control
Event place :
Melbourne, Australia
Event date :
from 12-12-2017 to 15-12-2017
Audience :
International
Main work title :
On definition and inference of nonlinear Boolean dynamic networks
Publisher :
IEEE
ISBN/EAN :
978-1-5090-2873-3
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
since 27 February 2018

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