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

Hufsky, F., Lamkiewicz, K., Almeida, A., Aouacheria, A., Arighi, C., Bateman, A., et al. (2020). Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and Coronavirus research. Briefings in Bioinformatics, bbaa232. doi:10.1093/bib/bbaa232.

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Externe Referenzen

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externe Referenz:
bioinformatics tools (Ergänzendes Material)
Beschreibung:
collected list of bioinformatics tools designed explicitly for SARS-CoV-2 and coronaviruses
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Urheber

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 Urheber:
Hufsky, Franziska, Autor
Lamkiewicz, Kevin, Autor
Almeida, Alexandre, Autor
Aouacheria, Abdel, Autor
Arighi, Cecilia, Autor
Bateman, Alex, Autor
Baumbach, Jan, Autor
Beerenwinkel, Niko, Autor
Brandt, Christian, Autor
Cacciabue, Marco, Autor
Chuguransky, Sara, Autor
Drechsel, Oliver, Autor
Finn, Robert D., Autor
Fritz, Adrian, Autor
Fuchs, Stephan, Autor
Hattab, Georges, Autor
Hauschild, Anne-Christin, Autor
Heider, Dominik, Autor
Hoffmann, Marie, Autor
Hölzer, Martin, Autor
Hoops, Stefan, AutorKaderali, Lars, AutorKalvari, Ioanna, Autorvon Kleist, Max, AutorKmiecinski, René, AutorKühnert, Denise1, Autor           Lasso, Gorka, AutorLibin, Pieter, AutorList, Markus, AutorLöchel, Hannah F., AutorMartin, Maria J., AutorMartin, Roman, AutorMatschinske, Julian, AutorMcHardy, Alice C., AutorMendes, Pedro, AutorMistry, Jaina, AutorNavratil, Vincent, AutorNawrocki, Eric, AutorO'Toole, Áine Niamh, AutorPalacios-Ontiveros, Nancy, AutorPetrov, Anton I., AutorRangel-Piñeros, Guillermo, AutorRedaschi, Nicole, AutorReimering, Susanne, AutorReinert, Knut, AutorReyes, Alejandro, AutorRichardson, Lorna, AutorRobertson, David L., AutorSadegh, Sepideh, AutorSinger, Joshua B., AutorTheys, Kristof, AutorUpton, Chris, AutorWelzel, Marius, AutorWilliams, Lowri, AutorMarz, Manja, Autor mehr..
Affiliations:
1tide, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2591691              

Inhalt

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Schlagwörter: virus bioinformatics, SARS-CoV-2, sequencing, epidemiology, drug design, tools
 Zusammenfassung: 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.

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Sprache(n): eng - English
 Datum: 2020-11-04
 Publikationsstatus: Online veröffentlicht
 Seiten: 22
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: 1 Introduction

2 Detection and annotation
2.1 PriSeT: Primer Search Tool
2.2 CoVPipe: Amplicon-based genome reconstruction
2.3 poreCov: Rapid sample analysis for nanopore sequencing
2.4 VADR: SARS-CoV-2 genome annotation and validation
2.5 V-Pipe: Calling single-nucleotide variants and viral haplotypes
2.6 Haploflow: Multi-strain aware de novo assembly
2.7 VIRify: Annotation of viruses in meta-omic data
2.8 Genome analysis tools by VBRC
2.9 VIRULIGN: Codon-correct multiple sequence alignments
2.10 Rfam COVID-19 Resources: Coronavirusspecific RNA families
2.11 UniProt COVID-19 protein portal: rapid access to protein information
2.12 Pfam protein families database

3 Tracking, epidemiology and evolution
3.1 Covidex: Alignment-free subtyping using machine learning
3.2 Pangolin: Phylogenetic Assignment of Named Global Outbreak LINeages
3.3 BEAST2: Phylodynamics based on Bayesian inference
3.4 Phylogeographic reconstruction using air transportation data
3.5 COPASI: Modeling SARS-CoV-2 dynamics with differential equations
3.6 COVIDSIM: Epidemiological models of viral spread
3.7 CoV-GLUE: tracking nucleotide changes in the SARS-CoV-2 genome
3.8 PoSeiDon: Positive Selection Detection and Recombination Analysis

4 Drug design
4.1 VirHostNet SARS-CoV-2 release
4.2 CORDITE: CORona Drug InTERactions database
4.3 CoVex: CoronaVirus Explorer
4.4 P-HIPSTer: a virus-host protein-protein interaction resource

5 Concluding remarks
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1093/bib/bbaa232
DOI: 10.20944/preprints202005.0376.v1
Anderer: shh2710
 Art des Abschluß: -

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Quelle 1

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Titel: Briefings in Bioinformatics
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: London : H. Stewart Publications
Seiten: - Band / Heft: - Artikelnummer: bbaa232 Start- / Endseite: - Identifikator: ISSN: 1467-5463
CoNE: https://pure.mpg.de/cone/journals/resource/974392606063

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Titel: Preprints.org
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: Basel : MPDI
Seiten: - Band / Heft: - Artikelnummer: 0376.v1 Start- / Endseite: - Identifikator: URN: https://www.preprints.org/