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

Franziska Hufsky | Kevin Lamkiewicz | Alexandre Almeida | Abdel Aouacheria | Cecilia Arighi | Alex Bateman | Jan Baumbach | Niko Beerenwinkel | Christian Brandt | Marco Cacciabue | Sara Chuguransky | Oliver Drechsel | Robert D Finn | Adrian Fritz | Stephan Fuchs | Georges Hattab | Anne-Christin Hauschild | Dominik Heider | Marie Hoffmann | Martin Hölzer | Stefan Hoops | Lars Kaderali | Ioanna Kalvari | Max von Kleist | Renó Kmiecinski | Denise Kühnert | Gorka Lasso | Pieter Libin | Markus List | Hannah F Löchel | Maria J Martin | Roman Martin | Julian Matschinske | Alice C McHardy | Pedro Mendes | Jaina Mistry | Vincent Navratil | Eric P Nawrocki | Áine Niamh O'Toole | Nancy Ontiveros-Palacios | Anton I Petrov | Guillermo Rangel-Pineros | Nicole Redaschi | Susanne Reimering | Knut Reinert | Alejandro Reyes | Lorna Richardson | David L Robertson | Sepideh Sadegh | Joshua B Singer | Kristof Theys | Chris Upton | Marius Welzel | Lowri Williams | Manja Marz
Briefings in bioinformatics | 2021

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.

Pubmed ID: 33147627 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NIGMS NIH HHS, United States
    Id: R01 GM080219
  • Agency: Wellcome Trust, United Kingdom
  • Agency: Medical Research Council, United Kingdom
    Id: MC_UU_12014/12
  • Agency: Medical Research Council, United Kingdom
    Id: MC_PC_19026
  • Agency: NIAID NIH HHS, United States
    Id: U19 AI142777
  • Agency: NHGRI NIH HHS, United States
    Id: U24 HG007822

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


ClinicalTrials.gov (tool)

RRID:SCR_002309

Registry and results database of federally and privately supported clinical trials conducted in United States and around world. Provides information about purpose of trial, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.Offers information for locating federally and privately supported clinical trials for wide range of diseases and conditions. Research study in human volunteers to answer specific health questions. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people or populations in natural settings. ClinicalTrials.gov contains trials sponsored by National Institutes of Health, other federal agencies, and private industry. Studies listed in database are conducted in all 50 States and in 178 countries.

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bioRxiv (tool)

RRID:SCR_003933

A free archive and distribution service for unpublished preprints in the life sciences allowing authors to make their findings immediately available to the scientific community and receive feedback on draft manuscripts before they are submitted to journals. An article may be posted prior to, or concurrently with, submission to a journal but should not be posted if it has already been published. Once an article is published in a journal, bioRxiv will update the preprint with a link to the published version.

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Pfam (tool)

RRID:SCR_004726

A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).

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COPASI (tool)

RRID:SCR_014260

Software application for simulation and analysis of biochemical network models and their dynamics. COPASI supports models in the SBML standard and can simulate their behavior using ODEs or Gillespies stochastic simulation algorithm. Arbitrary discrete events can be included in such simulations. Models in COPASI are based on reactions that convert a set of species into another set of species. Simulation can be performed either with stochastic kinetics or with differential equations. COPASI also includes various methods of analysis and data visualization.

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BEAST2 (tool)

RRID:SCR_017307

Software package for advanced Bayesian evolutionary analysis by sampling trees. Used for phylogenetics, population genetics and phylodynamics. Program for Bayesian phylogenetic analysis of molecular sequences. Estimates rooted, time measured phylogenies using strict or relaxed molecular clock models. Framework can be extended by third parties. Comprised of standalone programs including BEAUti, BEAST, MASTER, RBS, SNAPP, MultiTypeTree, BDSKY, LogAnalyser, LogCombiner, TreeAnnotator, DensiTree and package manager.

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medRxiv (tool)

RRID:SCR_018222

Free online archive and distribution server for complete but unpublished manuscripts in the medical, clinical, and related health sciences. Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health related behavior and should not be reported in news media as established information. Research articles, systematic reviews and meta analyses, clinical research design protocols and data articles may be posted.

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Global Initiative on Sharing All Influenza Data (tool)

RRID:SCR_018251

Portal to share hCoV-19 genome sequences. Collection of genome sequences and related clinical and epidemiological data associated with coronavirus hCoV-19. Global repository of SARS-CoV-2 genomes. Initiative involves public-private-partnerships between Freunde of GISAID and governments of Federal Republic of Germany, Singapore and United States of America, with support from private and corporate philanthropy.International database of hCoV-19 genome sequences and related clinical and epidemiological data. Resource for influenza and hCoV-19 data.

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