Evidence map›Paper›PMID 33057582›Full record

ArticleBriefings in bioinformatics2021

Web tools to fight pandemics: the COVID-19 experience.

Daniele Mercatelli, Andrew N Holding, Federico M Giorgi

Abstract read
In one paragraph

Article 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 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Ethnobotanical Study of Medicinal Plants Used against COVID-19.Evidence-based complementary and alternative medicine : eCAM · 2022
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Molecular Basis of the Therapeutical Potential of Clove (Molecules (Basel, Switzerland) · 2021
    Review
  16. Review
  17. Article
  18. Review
  19. 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

3 authors.

Daniele MercatelliUniversity of Bologna.
Andrew N HoldingUniversity of York.
Federico M GiorgiUniversity of Bologna.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.

Indexed as

PandemicsComputational BiologyCOVID-19HumansInternetSARS-CoV-2COVID-19epidemiologygenomicsinteractomicsSARS-CoV-2web tools

Identifiers

PMID33057582
PMCPMC7665357

What OpenQuestion 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 OpenQuestion graph.