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Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators

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Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators. / Rowland Adams, Joe; Stefanovska, Aneta.
2019-20 MATRIX Annals. ed. / David R. Wood; Jan de Gier; Cheryl E. Praeger; Terence Tao. Cham: Springer, 2021. p. 255-264 (Matrix Book Series; Vol. 4).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

Harvard

Rowland Adams, J & Stefanovska, A 2021, Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators. in DR Wood, J de Gier, CE Praeger & T Tao (eds), 2019-20 MATRIX Annals. Matrix Book Series, vol. 4, Springer, Cham, pp. 255-264. https://doi.org/10.1007/978-3-030-62497-2_13

APA

Rowland Adams, J., & Stefanovska, A. (2021). Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators. In D. R. Wood, J. de Gier, C. E. Praeger, & T. Tao (Eds.), 2019-20 MATRIX Annals (pp. 255-264). (Matrix Book Series; Vol. 4). Springer. https://doi.org/10.1007/978-3-030-62497-2_13

Vancouver

Rowland Adams J, Stefanovska A. Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators. In Wood DR, de Gier J, Praeger CE, Tao T, editors, 2019-20 MATRIX Annals. Cham: Springer. 2021. p. 255-264. (Matrix Book Series). Epub 2021 Feb 11. doi: 10.1007/978-3-030-62497-2_13

Author

Rowland Adams, Joe ; Stefanovska, Aneta. / Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators. 2019-20 MATRIX Annals. editor / David R. Wood ; Jan de Gier ; Cheryl E. Praeger ; Terence Tao. Cham : Springer, 2021. pp. 255-264 (Matrix Book Series).

Bibtex

@inbook{36dcc1b1e4634e2cbe1283f2136c7590,
title = "Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators",
abstract = "Oscillations are a common feature throughout life, forming a key mechanism by which living systems can regulate their internal processes and exchange information. To understand the functions and behaviours of these processes, we must understand the nature of their oscillations. Studying oscillations can be difficult within existing physical models that simulate the changes in a system{\textquoteright}s masses through autonomous differential equations. We discuss an alternative approach that focuses on the phases of oscillating processes and incorporates time as a key consideration. We will also consider the application of these theories to the cell energy metabolic system, and present a novel model using weighted nonautonomous Kuramoto oscillator networks in this context.",
author = "{Rowland Adams}, Joe and Aneta Stefanovska",
year = "2021",
month = feb,
day = "23",
doi = "10.1007/978-3-030-62497-2_13",
language = "English",
isbn = "9783030624965",
series = "Matrix Book Series",
publisher = "Springer",
pages = "255--264",
editor = "Wood, {David R.} and {de Gier}, Jan and Praeger, {Cheryl E.} and Terence Tao",
booktitle = "2019-20 MATRIX Annals",

}

RIS

TY - CHAP

T1 - Modelling Oscillating Living Systems: Cell Energy Metabolism as Weighted Networks of Nonautonomous Oscillators

AU - Rowland Adams, Joe

AU - Stefanovska, Aneta

PY - 2021/2/23

Y1 - 2021/2/23

N2 - Oscillations are a common feature throughout life, forming a key mechanism by which living systems can regulate their internal processes and exchange information. To understand the functions and behaviours of these processes, we must understand the nature of their oscillations. Studying oscillations can be difficult within existing physical models that simulate the changes in a system’s masses through autonomous differential equations. We discuss an alternative approach that focuses on the phases of oscillating processes and incorporates time as a key consideration. We will also consider the application of these theories to the cell energy metabolic system, and present a novel model using weighted nonautonomous Kuramoto oscillator networks in this context.

AB - Oscillations are a common feature throughout life, forming a key mechanism by which living systems can regulate their internal processes and exchange information. To understand the functions and behaviours of these processes, we must understand the nature of their oscillations. Studying oscillations can be difficult within existing physical models that simulate the changes in a system’s masses through autonomous differential equations. We discuss an alternative approach that focuses on the phases of oscillating processes and incorporates time as a key consideration. We will also consider the application of these theories to the cell energy metabolic system, and present a novel model using weighted nonautonomous Kuramoto oscillator networks in this context.

U2 - 10.1007/978-3-030-62497-2_13

DO - 10.1007/978-3-030-62497-2_13

M3 - Chapter

SN - 9783030624965

T3 - Matrix Book Series

SP - 255

EP - 264

BT - 2019-20 MATRIX Annals

A2 - Wood, David R.

A2 - de Gier, Jan

A2 - Praeger, Cheryl E.

A2 - Tao, Terence

PB - Springer

CY - Cham

ER -