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SleepOMICS: How Big Data Can Revolutionize Sleep Science

Author

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  • Nicola Luigi Bragazzi

    (Department of Health Sciences (DISSAL), Postgraduate School of Public Health, Genoa University, 16132 Genoa, Italy
    Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Genoa University, 16132 Genoa, Italy)

  • Ottavia Guglielmi

    (Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Genoa University, 16132 Genoa, Italy)

  • Sergio Garbarino

    (Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Genoa University, 16132 Genoa, Italy)

Abstract

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. “Real-life” behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level (“sleepOMICS”), thus paving the way for a targeted, “one-size-does-not-fit-all” management of sleep disorders (“precision sleep medicine”).

Suggested Citation

  • Nicola Luigi Bragazzi & Ottavia Guglielmi & Sergio Garbarino, 2019. "SleepOMICS: How Big Data Can Revolutionize Sleep Science," IJERPH, MDPI, vol. 16(2), pages 1-13, January.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:2:p:291-:d:199600
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    References listed on IDEAS

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    1. Sergio Garbarino & Paola Lanteri & Paolo Durando & Nicola Magnavita & Walter G. Sannita, 2016. "Co-Morbidity, Mortality, Quality of Life and the Healthcare/Welfare/Social Costs of Disordered Sleep: A Rapid Review," IJERPH, MDPI, vol. 13(8), pages 1-15, August.
    2. Benjamin D Yetton & Elizabeth A McDevitt & Nicola Cellini & Christian Shelton & Sara C Mednick, 2018. "Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-27, April.
    3. J. Allan Hobson, 2005. "Sleep is of the brain, by the brain and for the brain," Nature, Nature, vol. 437(7063), pages 1254-1256, October.
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    Cited by:

    1. Nicola Luigi Bragazzi & Haijiang Dai & Giovanni Damiani & Masoud Behzadifar & Mariano Martini & Jianhong Wu, 2020. "How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic," IJERPH, MDPI, vol. 17(9), pages 1-8, May.
    2. Jun Liu & Shuang Lai & Ayesha Akram Rai & Abual Hassan & Ray Tahir Mushtaq, 2023. "Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace," IJERPH, MDPI, vol. 20(5), pages 1-24, February.

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