Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research

Version 1 : Received: 22 May 2020 / Approved: 23 May 2020 / Online: 23 May 2020 (11:01:11 CEST)

How to cite: Hufsky, F.; Lamkiewicz, K.; Almeida, A.; Aouacheria, A.; Arighi, C.; Bateman, A.; Baumbach, J.; Beerenwinkel, N.; Brandt, C.; Cacciabue, M.; Chuguransky, S.; Drechsel, O.; Finn, R.D.; Fritz, A.; Fuchs, S.; Hattab, G.; Hauschild, A.; Heider, D.; Hoffmann, M.; Hölzer, M.; Hoops, S.; Kaderali, L.; Kalvari, I.; von Kleist, M.; Kmiecinski, R.; Kühnert, D.; Lasso, G.; Libin, P.; List, M.; Löchel, H.F.; Martin, M.J.; Martin, R.; Matschinske, J.; McHardy, A.C.; Mendes, P.; Mistry, J.; Navratil, V.; Nawrocki, E.; O'Toole, Á.N.; Palacios-Ontiveros, N.; Petrov, A.I.; Rangel-Piñeros, G.; Redaschi, N.; Reimering, S.; Reinert, K.; Reyes, A.; Richardson, L.; Robertson, D.L.; Sadegh, S.; Singer, J.B.; Theys, K.; Upton, C.; Welzel, M.; Williams, L.; Marz, M. Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research. Preprints 2020, 2020050376 (doi: 10.20944/preprints202005.0376.v1). Hufsky, F.; Lamkiewicz, K.; Almeida, A.; Aouacheria, A.; Arighi, C.; Bateman, A.; Baumbach, J.; Beerenwinkel, N.; Brandt, C.; Cacciabue, M.; Chuguransky, S.; Drechsel, O.; Finn, R.D.; Fritz, A.; Fuchs, S.; Hattab, G.; Hauschild, A.; Heider, D.; Hoffmann, M.; Hölzer, M.; Hoops, S.; Kaderali, L.; Kalvari, I.; von Kleist, M.; Kmiecinski, R.; Kühnert, D.; Lasso, G.; Libin, P.; List, M.; Löchel, H.F.; Martin, M.J.; Martin, R.; Matschinske, J.; McHardy, A.C.; Mendes, P.; Mistry, J.; Navratil, V.; Nawrocki, E.; O'Toole, Á.N.; Palacios-Ontiveros, N.; Petrov, A.I.; Rangel-Piñeros, G.; Redaschi, N.; Reimering, S.; Reinert, K.; Reyes, A.; Richardson, L.; Robertson, D.L.; Sadegh, S.; Singer, J.B.; Theys, K.; Upton, C.; Welzel, M.; Williams, L.; Marz, M. Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research. Preprints 2020, 2020050376 (doi: 10.20944/preprints202005.0376.v1).

Abstract

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 freely available online, either through web applications or public code repositories.

Supplementary and Associated Material

http://evbc.uni-jena.de/tools/coronavirus-tools/: You can find a list of the presented tools and further tools on the EVBC website.

Subject Areas

virus bioinformatics; SARS-CoV-2; sequencing; epidemiology; drug design; tools

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