Mathematical modeling of circadian rhythms

Oct 18, 2018Wiley interdisciplinary reviews. Systems biology and medicine

Using math to understand daily biological rhythms

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Abstract

Mathematical models of circadian rhythms aim to enhance understanding and prediction of biological processes impacted by these ~24-hour cycles.

Circadian rhythms influence various biological processes, including body temperature, sleep/wake cycles, and disease susceptibility.
Individual cells contain circadian clocks, which interact to form emergent properties at tissue and organism levels.
Mathematical models can manipulate circadian systems in a cost-effective manner, surpassing traditional experimental methods.
These models help resolve contradictory empirical results and generate new hypotheses and experimental designs.
Different models vary in structure, assumptions, parameters, and constraints, reflecting the complexity of circadian rhythms across species.

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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.

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Mathematical modeling of circadian rhythms

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