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Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure

Keul, Frank ; Hamacher, Kay (2022)
Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure.
In: Entropy, 2022, 24 (4)
doi: 10.26083/tuprints-00021285
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

Natural systems often show complex dynamics. The quantification of such complex dynamics is an important step in, e.g., characterization and classification of different systems or to investigate the effect of an external perturbation on the dynamics. Promising routes were followed in the past using concepts based on (Shannon’s) entropy. Here, we propose a new, conceptually sound measure that can be pragmatically computed, in contrast to pure theoretical concepts based on, e.g., Kolmogorov complexity. We illustrate the applicability using a toy example with a control parameter and go on to the molecular evolution of the HIV1 protease for which drug treatment can be regarded as an external perturbation that changes the complexity of its molecular evolutionary dynamics. In fact, our method identifies exactly those residues which are known to bind the drug molecules by their noticeable signal. We furthermore apply our method in a completely different domain, namely foreign exchange rates, and find convincing results as well.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Keul, Frank ; Hamacher, Kay
Art des Eintrags: Zweitveröffentlichung
Titel: Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure
Sprache: Englisch
Publikationsjahr: 2022
Publikationsdatum der Erstveröffentlichung: 2022
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Entropy
Jahrgang/Volume einer Zeitschrift: 24
(Heft-)Nummer: 4
Kollation: 9 Seiten
DOI: 10.26083/tuprints-00021285
URL / URN: https://tuprints.ulb.tu-darmstadt.de/21285
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Herkunft: Zweitveröffentlichung DeepGreen
Kurzbeschreibung (Abstract):

Natural systems often show complex dynamics. The quantification of such complex dynamics is an important step in, e.g., characterization and classification of different systems or to investigate the effect of an external perturbation on the dynamics. Promising routes were followed in the past using concepts based on (Shannon’s) entropy. Here, we propose a new, conceptually sound measure that can be pragmatically computed, in contrast to pure theoretical concepts based on, e.g., Kolmogorov complexity. We illustrate the applicability using a toy example with a control parameter and go on to the molecular evolution of the HIV1 protease for which drug treatment can be regarded as an external perturbation that changes the complexity of its molecular evolutionary dynamics. In fact, our method identifies exactly those residues which are known to bind the drug molecules by their noticeable signal. We furthermore apply our method in a completely different domain, namely foreign exchange rates, and find convincing results as well.

Freie Schlagworte: complexity, co-evolution, Jensen–Shannon, entropy
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-212856
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie
Fachbereich(e)/-gebiet(e): 10 Fachbereich Biologie
10 Fachbereich Biologie > Computational Biology and Simulation
Hinterlegungsdatum: 09 Mai 2022 13:45
Letzte Änderung: 10 Mai 2022 05:16
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