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

Research output: Contribution to journalReviewResearchpeer-review

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Computational strategies to combat COVID-19 : useful tools to accelerate SARS-CoV-2 and coronavirus research. / Hufsky, Franziska; Lamkiewicz, Kevin; Almeida, Alexandre; Aouacheria, Abdel; Arighi, Cecilia; Bateman, Alex; Baumbach, Jan; Beerenwinkel, Niko; Brandt, Christian; Cacciabue, Marco; Chuguransky, Sara; Drechsel, Oliver; Finn, Robert D.; Fritz, Adrian; Fuchs, Stephan; Hattab, Georges; Hauschild, Anne-Christin; Heider, Dominik; Hoffmann, Marie; Hölzer, Martin; Hoops, Stefan; Kaderali, Lars; Kalvari, Ioanna; von Kleist, Max; Kmiecinski, Renó; Kühnert, Denise; Lasso, Gorka; Libin, Pieter; List, Markus; Löchel, Hannah F.; Martin, Maria J.; Martin, Roman; Matschinske, Julian; McHardy, Alice C.; Mendes, Pedro; Mistry, Jaina; Navratil, Vincent; Nawrocki, Eric P.; O'Toole, Aíne Niamh; Ontiveros-Palacios, Nancy; Petrov, Anton I.; Rangel-Pineros, Guillermo; Redaschi, Nicole; Reimering, Susanne; Reinert, Knut; Reyes, Alejandro; Richardson, Lorna; Robertson, David L.; Sadegh, Sepideh; Singer, Joshua B.; Theys, Kristof; Upton, Chris; Welzel, Marius; Williams, Lowri; Marz, Manja.

In: Briefings in Bioinformatics, Vol. 22, No. 2, 2021, p. 642-663.

Research output: Contribution to journalReviewResearchpeer-review

Harvard

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, RD, Fritz, A, Fuchs, S, Hattab, G, Hauschild, A-C, 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, HF, Martin, MJ, Martin, R, Matschinske, J, McHardy, AC, Mendes, P, Mistry, J, Navratil, V, Nawrocki, EP, O'Toole, AN, Ontiveros-Palacios, N, Petrov, AI, Rangel-Pineros, G, Redaschi, N, Reimering, S, Reinert, K, Reyes, A, Richardson, L, Robertson, DL, Sadegh, S, Singer, JB, Theys, K, Upton, C, Welzel, M, Williams, L & Marz, M 2021, 'Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research', Briefings in Bioinformatics, vol. 22, no. 2, pp. 642-663. https://doi.org/10.1093/bib/bbaa232

APA

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-C., Heider, D., Hoffmann, M., ... Marz, M. (2021). Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Briefings in Bioinformatics, 22(2), 642-663. https://doi.org/10.1093/bib/bbaa232

Vancouver

Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A et al. Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Briefings in Bioinformatics. 2021;22(2):642-663. https://doi.org/10.1093/bib/bbaa232

Author

Hufsky, Franziska ; Lamkiewicz, Kevin ; Almeida, Alexandre ; Aouacheria, Abdel ; Arighi, Cecilia ; Bateman, Alex ; Baumbach, Jan ; Beerenwinkel, Niko ; Brandt, Christian ; Cacciabue, Marco ; Chuguransky, Sara ; Drechsel, Oliver ; Finn, Robert D. ; Fritz, Adrian ; Fuchs, Stephan ; Hattab, Georges ; Hauschild, Anne-Christin ; Heider, Dominik ; Hoffmann, Marie ; Hölzer, Martin ; Hoops, Stefan ; Kaderali, Lars ; Kalvari, Ioanna ; von Kleist, Max ; Kmiecinski, Renó ; Kühnert, Denise ; Lasso, Gorka ; Libin, Pieter ; List, Markus ; Löchel, Hannah F. ; Martin, Maria J. ; Martin, Roman ; Matschinske, Julian ; McHardy, Alice C. ; Mendes, Pedro ; Mistry, Jaina ; Navratil, Vincent ; Nawrocki, Eric P. ; O'Toole, Aíne Niamh ; Ontiveros-Palacios, Nancy ; Petrov, Anton I. ; Rangel-Pineros, Guillermo ; Redaschi, Nicole ; Reimering, Susanne ; Reinert, Knut ; Reyes, Alejandro ; Richardson, Lorna ; Robertson, David L. ; Sadegh, Sepideh ; Singer, Joshua B. ; Theys, Kristof ; Upton, Chris ; Welzel, Marius ; Williams, Lowri ; Marz, Manja. / Computational strategies to combat COVID-19 : useful tools to accelerate SARS-CoV-2 and coronavirus research. In: Briefings in Bioinformatics. 2021 ; Vol. 22, No. 2. pp. 642-663.

Bibtex

@article{75779ae5b3ad41dd98aad8615b327d86,
title = "Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research",
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 free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de ",
keywords = "drug design, epidemiology, SARS-CoV-2, sequencing, tools, virus bioinformatics",
author = "Franziska Hufsky and Kevin Lamkiewicz and Alexandre Almeida and Abdel Aouacheria and Cecilia Arighi and Alex Bateman and Jan Baumbach and Niko Beerenwinkel and Christian Brandt and Marco Cacciabue and Sara Chuguransky and Oliver Drechsel and Finn, {Robert D.} and Adrian Fritz and Stephan Fuchs and Georges Hattab and Anne-Christin Hauschild and Dominik Heider and Marie Hoffmann and Martin H{\"o}lzer and Stefan Hoops and Lars Kaderali and Ioanna Kalvari and {von Kleist}, Max and Ren{\'o} Kmiecinski and Denise K{\"u}hnert and Gorka Lasso and Pieter Libin and Markus List and L{\"o}chel, {Hannah F.} and Martin, {Maria J.} and Roman Martin and Julian Matschinske and McHardy, {Alice C.} and Pedro Mendes and Jaina Mistry and Vincent Navratil and Nawrocki, {Eric P.} and O'Toole, {A{\'i}ne Niamh} and Nancy Ontiveros-Palacios and Petrov, {Anton I.} and Guillermo Rangel-Pineros and Nicole Redaschi and Susanne Reimering and Knut Reinert and Alejandro Reyes and Lorna Richardson and Robertson, {David L.} and Sepideh Sadegh and Singer, {Joshua B.} and Kristof Theys and Chris Upton and Marius Welzel and Lowri Williams and Manja Marz",
year = "2021",
doi = "10.1093/bib/bbaa232",
language = "English",
volume = "22",
pages = "642--663",
journal = "Briefings in Bioinformatics",
issn = "1467-5463",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Computational strategies to combat COVID-19

T2 - useful tools to accelerate SARS-CoV-2 and coronavirus research

AU - Hufsky, Franziska

AU - Lamkiewicz, Kevin

AU - Almeida, Alexandre

AU - Aouacheria, Abdel

AU - Arighi, Cecilia

AU - Bateman, Alex

AU - Baumbach, Jan

AU - Beerenwinkel, Niko

AU - Brandt, Christian

AU - Cacciabue, Marco

AU - Chuguransky, Sara

AU - Drechsel, Oliver

AU - Finn, Robert D.

AU - Fritz, Adrian

AU - Fuchs, Stephan

AU - Hattab, Georges

AU - Hauschild, Anne-Christin

AU - Heider, Dominik

AU - Hoffmann, Marie

AU - Hölzer, Martin

AU - Hoops, Stefan

AU - Kaderali, Lars

AU - Kalvari, Ioanna

AU - von Kleist, Max

AU - Kmiecinski, Renó

AU - Kühnert, Denise

AU - Lasso, Gorka

AU - Libin, Pieter

AU - List, Markus

AU - Löchel, Hannah F.

AU - Martin, Maria J.

AU - Martin, Roman

AU - Matschinske, Julian

AU - McHardy, Alice C.

AU - Mendes, Pedro

AU - Mistry, Jaina

AU - Navratil, Vincent

AU - Nawrocki, Eric P.

AU - O'Toole, Aíne Niamh

AU - Ontiveros-Palacios, Nancy

AU - Petrov, Anton I.

AU - Rangel-Pineros, Guillermo

AU - Redaschi, Nicole

AU - Reimering, Susanne

AU - Reinert, Knut

AU - Reyes, Alejandro

AU - Richardson, Lorna

AU - Robertson, David L.

AU - Sadegh, Sepideh

AU - Singer, Joshua B.

AU - Theys, Kristof

AU - Upton, Chris

AU - Welzel, Marius

AU - Williams, Lowri

AU - Marz, Manja

PY - 2021

Y1 - 2021

N2 - 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

AB - 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

KW - drug design

KW - epidemiology

KW - SARS-CoV-2

KW - sequencing

KW - tools

KW - virus bioinformatics

U2 - 10.1093/bib/bbaa232

DO - 10.1093/bib/bbaa232

M3 - Review

C2 - 33147627

AN - SCOPUS:85103474550

VL - 22

SP - 642

EP - 663

JO - Briefings in Bioinformatics

JF - Briefings in Bioinformatics

SN - 1467-5463

IS - 2

ER -

ID: 272718906