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A review on viral data sources and search systems for perspective mitigation of COVID-19.
Bernasconi, Anna; Canakoglu, Arif; Masseroli, Marco; Pinoli, Pietro; Ceri, Stefano.
Afiliación
  • Bernasconi A; Politecnico di Milano.
  • Canakoglu A; Politecnico di Milano.
  • Masseroli M; Politecnico di Milano.
  • Pinoli P; Politecnico di Milano.
  • Ceri S; Politecnico di Milano.
Brief Bioinform ; 22(2): 664-675, 2021 03 22.
Article en En | MEDLINE | ID: mdl-33348368
ABSTRACT
With the outbreak of the COVID-19 disease, the research community is producing unprecedented efforts dedicated to better understand and mitigate the effects of the pandemic. In this context, we review the data integration efforts required for accessing and searching genome sequences and metadata of SARS-CoV2, the virus responsible for the COVID-19 disease, which have been deposited into the most important repositories of viral sequences. Organizations that were already present in the virus domain are now dedicating special interest to the emergence of COVID-19 pandemics, by emphasizing specific SARS-CoV2 data and services. At the same time, novel organizations and resources were born in this critical period to serve specifically the purposes of COVID-19 mitigation while setting the research ground for contrasting possible future pandemics. Accessibility and integration of viral sequence data, possibly in conjunction with the human host genotype and clinical data, are paramount to better understand the COVID-19 disease and mitigate its effects. Few examples of host-pathogen integrated datasets exist so far, but we expect them to grow together with the knowledge of COVID-19 disease; once such datasets will be available, useful integrative surveillance mechanisms can be put in place by observing how common variants distribute in time and space, relating them to the phenotypic impact evidenced in the literature.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article