A Web Application for Biomedical Text Mining of Scientific Literature Associated with Coronavirus-Related Syndromes: Coronavirus Finder

In this study, a web application was developed that comprises scientific literature associated with the family, specifically for those viruses that are members of the Genus Betacoronavirus, responsible for emerging diseases with a great impact on human health: Middle East Respiratory Syndrome-Relate...

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Bibliographic Details
Published in:Diagnostics (Basel) 2022-04, Vol.12 (4), p.887
Main Authors: Armenta-Medina, Dagoberto, Brambila-Tapia, Aniel Jessica Leticia, Miranda-Jiménez, Sabino, Rodea-Montero, Edel Rafael
Format: Article
Language:English
Subjects:
coronavirus
Coronaviruses
COVID-19
latent semantic analysis
MERS
Middle East respiratory syndrome
natural language processing
Respiratory diseases
SARS
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Summary:In this study, a web application was developed that comprises scientific literature associated with the family, specifically for those viruses that are members of the Genus Betacoronavirus, responsible for emerging diseases with a great impact on human health: Middle East Respiratory Syndrome-Related Coronavirus (MERS-CoV) and Severe Acute Respiratory Syndrome-Related Coronavirus (SARS-CoV, SARS-CoV-2). The information compiled on this webserver aims to understand the basics of these viruses' infection, and the nature of their pathogenesis, enabling the identification of molecular and cellular components that may function as potential targets on the design and development of successful treatments for the diseases associated with the family. Some of the web application's primary functions are searching for keywords within the scientific literature, natural language processing for the extraction of genes and words, the generation and visualization of gene networks associated with viral diseases derived from the analysis of latent semantic space, and cosine similarity measures. Interestingly, our gene association analysis reveals drug targets in understudies, and new targets suggested in the scientific literature to treat coronavirus.
ISSN:2075-4418
2075-4418
DOI:10.3390/diagnostics12040887