Evidence map›Paper›PMID 33348368›Full record

ReviewBriefings in bioinformatics2021

A review on viral data sources and search systems for perspective mitigation of COVID-19.

Anna Bernasconi, Arif Canakoglu, Marco Masseroli, Pietro Pinoli, Stefano Ceri

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025
    Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
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  10. Article
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  13. COVID-19: why not learn from the past?Frontiers of medicine · 2021
    Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anna BernasconiPolitecnico di Milano.
Arif CanakogluPolitecnico di Milano.
Marco MasseroliPolitecnico di Milano.
Pietro PinoliPolitecnico di Milano.
Stefano CeriPolitecnico di Milano.

Funding

European Research Council
6 · The paper itself

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.

Indexed as

COVID-19Genes, ViralHumansInformation Storage and RetrievalPandemicsSARS-CoV-2COVID-19data harmonizationepidemicgenomicsintegration and searchmetadataviral sequences

Identifiers

PMID33348368
PMCPMC7799334

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.