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1000 Titel
  • COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response
1000 Autor/in
  1. Yu, Wei |
  2. Drzymalla, Emily |
  3. Gwinn, Marta |
  4. Khoury, Muin J. |
1000 Erscheinungsjahr 2022
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2022-04-25
1000 Erschienen in
1000 Quellenangabe
  • 22(1):402
1000 Copyrightjahr
  • 2022
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12879-022-07219-3 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035978/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The scientific response to the COVID-19 pandemic has produced an abundance of publications, including peer-reviewed articles and preprints, across a wide array of disciplines, from microbiology to medicine and social sciences. Genomics and precision health (GPH) technologies have had a particularly prominent role in medical and public health investigations and response; however, these domains are not simply defined and it is difficult to search for relevant information using traditional strategies. To quantify and track the ongoing contributions of GPH to the COVID-19 response, the Office of Genomics and Precision Public Health at the Centers for Disease Control and Prevention created the COVID-19 Genomics and Precision Health database (COVID-19 GPH), an open access knowledge management system and publications database that is continuously updated through machine learning and manual curation. As of February 11, 2022, COVID-GPH contained 31,597 articles, mostly on pathogen and human genomics (72%). The database also includes articles describing applications of machine learning and artificial intelligence to the investigation and control of COVID-19 (28%). COVID-GPH represents about 10% (22983/221241) of the literature on COVID-19 on PubMed. This unique knowledge management database makes it easier to explore, describe, and track how the pandemic response is accelerating the applications of genomics and precision health technologies. COVID-19 GPH can be freely accessed via https://phgkb.cdc.gov/PHGKB/coVInfoStartPage.action .
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Genomics
lokal Humans
lokal Humans [MeSH]
lokal SARS-CoV-2/genetics [MeSH]
lokal Artificial Intelligence
lokal Artificial Intelligence [MeSH]
lokal Infectious Diseases
lokal Pandemics
lokal Pandemics [MeSH]
lokal Genomics [MeSH]
lokal Precision Medicine [MeSH]
lokal COVID-19/epidemiology [MeSH]
lokal SARS-CoV-2/genetics
lokal Precision Medicine
lokal COVID-19/epidemiology
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/WXUsIFdlaQ==|https://frl.publisso.de/adhoc/uri/RHJ6eW1hbGxhLCBFbWlseQ==|https://frl.publisso.de/adhoc/uri/R3dpbm4sIE1hcnRh|https://frl.publisso.de/adhoc/uri/S2hvdXJ5LCBNdWluIEou
1000 Hinweis
  • Metadata provieded by: LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Dateien
1000 Objektart article
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1000 @id frl:6439421.rdf
1000 Erstellt am 2023-01-10T11:55:54.429+0100
1000 Erstellt von 336
1000 beschreibt frl:6439421
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Fri Apr 05 14:03:15 CEST 2024
1000 Objekt bearb. Tue Jan 10 11:57:02 CET 2023
1000 Vgl. frl:6439421
1000 Oai Id
  1. oai:frl.publisso.de:frl:6439421 |
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