CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement.
COVID-19
Citation maps
Literature mining
MeSH maps
Journal
Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369
Informations de publication
Date de publication:
Dec 2024
Dec 2024
Historique:
received:
10
04
2024
revised:
19
06
2024
accepted:
19
06
2024
medline:
19
7
2024
pubmed:
19
7
2024
entrez:
19
7
2024
Statut:
epublish
Résumé
During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature. We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks. We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and their associations. CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research.
Sections du résumé
Background
UNASSIGNED
During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature.
Objectives
UNASSIGNED
We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks.
Methods
UNASSIGNED
We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and their associations.
Results
UNASSIGNED
CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications.
Conclusion
UNASSIGNED
CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research.
Identifiants
pubmed: 39027652
doi: 10.1016/j.csbj.2024.06.018
pii: S2001-0370(24)00217-4
pmc: PMC11254833
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2661-2668Informations de copyright
© 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.