Evidence map›Paper›PMID 36511598›Full record

ArticleBioinformatics (Oxford, England)2023

COVoc and COVTriage: novel resources to support literature triage.

Déborah Caucheteur, Zoë May Pendlington, Paola Roncaglia, Julien Gobeill, Luc Mottin, Nicolas Matentzoglu, Donat Agosti, David Osumi-Sutherland, Helen Parkinson, Patrick Ruch

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Enhancing the SIB Literature Services (SIBiLS) with annotations to support biocuration.Database : the journal of biological databases and curation · 2026
    Article
  2. Review
  3. Europe PMC in 2023.Nucleic acids research · 2024
    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

10 authors.

Déborah CaucheteurSIB Text Mining Group, Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.ORCID 0000-0003-0800-544X
Zoë May PendlingtonEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.
Paola RoncagliaEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.
Julien GobeillSIB Text Mining Group, Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.ORCID 0000-0001-9809-7741
Luc MottinSIB Text Mining Group, Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.ORCID 0000-0002-9614-9293
Nicolas MatentzogluEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.
Donat AgostiSIB Text Mining Group, Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.
David Osumi-SutherlandEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.ORCID 0000-0002-7073-9172
Helen ParkinsonEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.
Patrick RuchSIB Text Mining Group, Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.

Funding

The Monarch Initiative: Linking Diseases to Model Organism ResourcesR24OD011883 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAENDEL, MELISSA A, MUNGALL, CHRISTOPHER J · 2012 to 2024
$16.0M
BICKL Research Project H2020-EU.1.4NIH HHS R24 OD011883
6 · The paper itself

Abstract

motivationSince early 2020, the coronavirus disease 2019 (COVID-19) pandemic has confronted the biomedical community with an unprecedented challenge. The rapid spread of COVID-19 and ease of transmission seen worldwide is due to increased population flow and international trade. Front-line medical care, treatment research and vaccine development also require rapid and informative interpretation of the literature and COVID-19 data produced around the world, with 177 500 papers published between January 2020 and November 2021, i.e. almost 8500 papers per month. To extract knowledge and enable interoperability across resources, we developed the COVID-19 Vocabulary (COVoc), an application ontology related to the research on this pandemic. The main objective of COVoc development was to enable seamless navigation from biomedical literature to core databases and tools of ELIXIR, a European-wide intergovernmental organization for life sciences.

resultsThis collaborative work provided data integration into SIB Literature services, an application ontology (COVoc) and a triage service named COVTriage and based on annotation processing to search for COVID-related information across pre-defined aspects with daily updates. Thanks to its interoperability potential, COVoc lends itself to wider applications, hopefully through further connections with other novel COVID-19 ontologies as has been established with Coronavirus Infectious Disease Ontology. AVAILABILITY AND IMPLEMENTATION: The data at https://github.com/EBISPOT/covoc and the service at https://candy.hesge.ch/COVTriage.

Indexed as

COVID-19CommerceHumansInternationalityTriage

Identifiers

PMID36511598
PMCPMC9825781

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.