Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Syst Biol Med
Impact Factor: 3.709

Mathematical modeling of circadian rhythms

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

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
An iterative process of model validation
[ Normal View | Magnified View ]
A schematic description of one method for developing a mathematical model. (Revised from the schema in Brown & Luithardt, ; Klerman & St Hilaire, )
[ Normal View | Magnified View ]
Illustrative examples of self‐sustained (a & b), damped (c & d), and excitable (e & f) oscillations for the Hodgkin‐Huxley model of a neuron, with variation in the potassium channel conductivity parameter. The left column shows the phase portraits (i.e., how variables evolve with respect to each other; note that time is implicit in the plot), while the right column shows how one variable (voltage) changes with time. For the self‐sustained oscillator, the model evolves to a closed limit cycle with a periodic output. For the damped oscillator, the model evolves to a steady state as the amplitude of the oscillation decays. For the excitable oscillator, a single cycle can be evoked, but the system thereafter returns to the steady state
[ Normal View | Magnified View ]

Browse by Topic

Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models
Physiology > Mammalian Physiology in Health and Disease

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts