Literature DB >> 30328684

Mathematical modeling of circadian rhythms.

Ameneh Asgari-Targhi1, Elizabeth B Klerman1.   

Abstract

Circadian rhythms are endogenous ~24-hr oscillations usually entrained to daily environmental cycles of light/dark. Many biological processes and physiological functions including mammalian body temperature, the cell cycle, sleep/wake cycles, neurobehavioral performance, and a wide range of diseases including metabolic, cardiovascular, and psychiatric disorders are impacted by these rhythms. Circadian clocks are present within individual cells and at tissue and organismal levels as emergent properties from the interaction of cellular oscillators. Mathematical models of circadian rhythms have been proposed to provide a better understanding of and to predict aspects of this complex physiological system. These models can be used to: (a) manipulate the system in silico with specificity that cannot be easily achieved using in vivo and in vitro experimental methods and at lower cost, (b) resolve apparently contradictory empirical results, (c) generate hypotheses, (d) design new experiments, and (e) to design interventions for altering circadian rhythms. Mathematical models differ in structure, the underlying assumptions, the number of parameters and variables, and constraints on variables. Models representing circadian rhythms at different physiologic scales and in different species are reviewed to promote understanding of these models and facilitate their use. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  biological oscillators; circadian clock; circadian rhythms; dynamic systems; mathematical modeling; statistical modeling

Mesh:

Substances:

Year:  2018        PMID: 30328684      PMCID: PMC6375788          DOI: 10.1002/wsbm.1439

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev Syst Biol Med        ISSN: 1939-005X


  167 in total

1.  Linear demasking techniques are unreliable for estimating the circadian phase of ambulatory temperature data.

Authors:  E B Klerman; Y Lee; C A Czeisler; R E Kronauer
Journal:  J Biol Rhythms       Date:  1999-08       Impact factor: 3.182

2.  Accuracy of circadian entrainment under fluctuating light conditions: contributions of phase and period responses.

Authors:  D G Beersma; S Daan; R A Hut
Journal:  J Biol Rhythms       Date:  1999-08       Impact factor: 3.182

3.  A single pacemaker can produce different rates of reentrainment in different overt rhythms.

Authors: 
Journal:  J Sleep Res       Date:  1992-06       Impact factor: 3.981

4.  Generation of activity-rest patterns by dual circadian pacemaker systems: a model.

Authors: 
Journal:  J Sleep Res       Date:  1992-06       Impact factor: 3.981

5.  Modeling circadian rhythm generation in the suprachiasmatic nucleus with locally coupled self-sustained oscillators: phase shifts and phase response curves.

Authors:  P Achermann; H Kunz
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

Review 6.  Revised limit cycle oscillator model of human circadian pacemaker.

Authors:  M E Jewett; D B Forger; R E Kronauer
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

7.  A simpler model of the human circadian pacemaker.

Authors:  D B Forger; M E Jewett; R E Kronauer
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

Review 8.  Quantifying human circadian pacemaker response to brief, extended, and repeated light stimuli over the phototopic range.

Authors:  R E Kronauer; D B Forger; M E Jewett
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

9.  Statistical model building and model criticism for human circadian data.

Authors:  E N Brown; H Luithardt
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

Review 10.  Limit cycle models for circadian rhythms based on transcriptional regulation in Drosophila and Neurospora.

Authors:  J C Leloup; D Gonze; A Goldbeter
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

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  6 in total

Review 1.  Circadian rhythms and the HPA axis: A systems view.

Authors:  Ioannis P Androulakis
Journal:  WIREs Mech Dis       Date:  2021-01-12

2.  Light-based methods for predicting circadian phase in delayed sleep-wake phase disorder.

Authors:  Jade M Murray; Michelle Magee; Tracey L Sletten; Christopher Gordon; Nicole Lovato; Krutika Ambani; Delwyn J Bartlett; David J Kennaway; Leon C Lack; Ronald R Grunstein; Steven W Lockley; Shantha M W Rajaratnam; Andrew J K Phillips
Journal:  Sci Rep       Date:  2021-05-25       Impact factor: 4.379

3.  Unstable eigenvectors and reduced amplitude spaces specifying limit cycles of coupled oscillators with simultaneously diagonalizable matrices: with applications from electric circuits to gene regulation.

Authors:  S Mongkolsakulvong; T D Frank
Journal:  Eur Phys J B       Date:  2022-09-19       Impact factor: 1.398

Review 4.  Mathematical modeling of mammalian circadian clocks affecting drug and disease responses.

Authors:  Panteleimon D Mavroudis; William J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-03-16       Impact factor: 2.410

5.  A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light.

Authors:  Vojtěch Kumpošt; Daniela Vallone; Srinivas Babu Gondi; Nicholas S Foulkes; Ralf Mikut; Lennart Hilbert
Journal:  Sci Rep       Date:  2021-07-14       Impact factor: 4.379

6.  Targeted modification of the Per2 clock gene alters circadian function in mPer2luciferase (mPer2Luc) mice.

Authors:  Martin R Ralph; Shu-Qun Shi; Carl H Johnson; Pavel Houdek; Tenjin C Shrestha; Priya Crosby; John S O'Neill; Martin Sládek; Adam R Stinchcombe; Alena Sumová
Journal:  PLoS Comput Biol       Date:  2021-05-28       Impact factor: 4.475

  6 in total

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