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SleepOMICS: How Big Data Can Revolutionize Sleep Science
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 impressiv...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351921/ https://www.ncbi.nlm.nih.gov/pubmed/30669659 http://dx.doi.org/10.3390/ijerph16020291 |
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author | Bragazzi, Nicola Luigi Guglielmi, Ottavia Garbarino, Sergio |
author_facet | Bragazzi, Nicola Luigi Guglielmi, Ottavia Garbarino, Sergio |
author_sort | Bragazzi, Nicola Luigi |
collection | PubMed |
description | 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”). |
format | Online Article Text |
id | pubmed-6351921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63519212019-02-01 SleepOMICS: How Big Data Can Revolutionize Sleep Science Bragazzi, Nicola Luigi Guglielmi, Ottavia Garbarino, Sergio Int J Environ Res Public Health Review 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”). MDPI 2019-01-21 2019-01 /pmc/articles/PMC6351921/ /pubmed/30669659 http://dx.doi.org/10.3390/ijerph16020291 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Bragazzi, Nicola Luigi Guglielmi, Ottavia Garbarino, Sergio SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title | SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title_full | SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title_fullStr | SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title_full_unstemmed | SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title_short | SleepOMICS: How Big Data Can Revolutionize Sleep Science |
title_sort | sleepomics: how big data can revolutionize sleep science |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351921/ https://www.ncbi.nlm.nih.gov/pubmed/30669659 http://dx.doi.org/10.3390/ijerph16020291 |
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