Classification and detection of Critical Transitions: from theory to data
English
Proverbio, Daniele[University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience >]
21-Oct-2022
University of Luxembourg, Luxembourg
Docteur en Sciences de l'Ingénieur
Goncalves, Jorge
Balling, Rudi
Skupin, Alexander
Ashwin, Peter
Cosentino Lagomarsino, Marco
[en] Critical transitions ; Resilience ; Complex systems ; Early warning signals ; Dynamics ; Systems biology ; Bifurcation ; Noise ; Modelling
[en] From population collapses to cell-fate decision, critical phenomena are abundant in complex real-world systems. Among modelling theories to address them, the critical transitions framework gained traction for its purpose of determining classes of critical mechanisms and identifying generic indicators to detect and alert them (“early warning signals”). This thesis contributes to such research field by elucidating its relevance within the systems biology landscape, by providing a systematic classification of leading mechanisms for critical transitions, and by assessing the theoretical and empirical performance of early warning signals. The thesis thus bridges general results concerning the critical transitions field – possibly applicable to multidisciplinary contexts – and specific applications in biology and epidemiology, towards the development of sound risk monitoring system.
Luxembourg Centre for Systems Biomedicine (LCSB)
Fonds National de la Recherche - FnR
CRiTiCS
Researchers ; Professionals ; Students ; General public