Reference : Optimising time-series experimental design for modelling of circadian rhythms: the va...
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Multidisciplinary, general & others
Systems Biomedicine
http://hdl.handle.net/10993/30748
Optimising time-series experimental design for modelling of circadian rhythms: the value of transient data
English
Mombaerts, Laurent mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Mauroy, Alexandre mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Oct-2016
IFAC-PapersOnLine
Elsevier
Yes (verified by ORBilu)
International
2405-8963
6th IFAC Conference on Foundations of Systems Biology in Engineering
from 09-10-2016 to 12-10-2016
Magdeburg
Germany
[en] Network Inference ; Modelling ; Circadian Rhythms
[en] Circadian clocks consist of complex networks that coordinate the daily cycle of most organisms. In light/dark cycles, the clock is synchronized (or entrained) by the environment, which corresponds to a constant rephasing of the oscillations and leads to a steady state regime. Some circadian clocks are endogenous oscillators with rhythms of about 24-hours that persist in constant light or constant darkness. This operating mechanism with and without entrainment provides flexibility and robustness to the clock against perturbations. Most of the clock-oriented experiments are performed under constant photoperiodic regime, overlooking the transitory regime that takes place between light/dark cycles and constant light or darkness. This paper provides a comparative analysis of the informative potential of the transient time-series data with the other regimes for clock modelling.
Realistic data were simulated from 2 experimentally validated plant circadian clock models and sliced into several time windows. These windows represent the different regimes that take place before, meanwhile and after the switch to constant light. Then, a network inference tool was used over each window and its capability of retrieving the ground-truth of the network was compared for each window. The results suggest that including the transient data to the network inference technique significally improves its performance.
http://hdl.handle.net/10993/30748

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