Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research

作者
Franziska Hufsky,Kevin Lamkiewicz,Alexandre Almeida,Abdel Aouacheria,Cecilia N. Arighi,Alex Bateman,Jan Baumbach,Niko Beerenwinkel,Christian Brandt,Marco Cacciabue,Sara Chuguransky,Oliver Drechsel,ROBERT FINN,Adrian Fritz,Stephan Fuchs,Georges Hattab,Anne-Christin Hauschild,Dominik Heider,Marie Hoffmann,Martin Hölzer
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:22 (2): 642-663 被引量:149
标识
DOI:10.1093/bib/bbaa232
摘要

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.

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