COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics.

Abstract:

:The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs' action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.

journal_name

Nucleic Acids Res

journal_title

Nucleic acids research

authors

Tworowski D,Gorohovski A,Mukherjee S,Carmi G,Levy E,Detroja R,Mukherjee SB,Frenkel-Morgenstern M

doi

10.1093/nar/gkaa969

subject

Has Abstract

pub_date

2021-01-08 00:00:00

pages

D1113-D1121

issue

D1

eissn

0305-1048

issn

1362-4962

pii

5964073

journal_volume

49

pub_type

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