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Open science resources for the mass spectrometry-based analysis of SARS-CoV-2

Bittremieux, Wout; Adams, Charlotte; Laukens, Kris; Dorrestein, Pieter C.; Bandeira, Nuno


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  <identifier identifierType="DOI">10.5281/zenodo.4552687</identifier>
  <creators>
    <creator>
      <creatorName>Bittremieux, Wout</creatorName>
      <givenName>Wout</givenName>
      <familyName>Bittremieux</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3105-1359</nameIdentifier>
      <affiliation>University of California San Diego</affiliation>
    </creator>
    <creator>
      <creatorName>Adams, Charlotte</creatorName>
      <givenName>Charlotte</givenName>
      <familyName>Adams</familyName>
      <affiliation>University of Antwerp</affiliation>
    </creator>
    <creator>
      <creatorName>Laukens, Kris</creatorName>
      <givenName>Kris</givenName>
      <familyName>Laukens</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8217-2564</nameIdentifier>
      <affiliation>University of Antwerp</affiliation>
    </creator>
    <creator>
      <creatorName>Dorrestein, Pieter C.</creatorName>
      <givenName>Pieter C.</givenName>
      <familyName>Dorrestein</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3003-1030</nameIdentifier>
      <affiliation>University of California San Diego</affiliation>
    </creator>
    <creator>
      <creatorName>Bandeira, Nuno</creatorName>
      <givenName>Nuno</givenName>
      <familyName>Bandeira</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8385-3655</nameIdentifier>
      <affiliation>University of California San Diego</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Open science resources for the mass spectrometry-based analysis of SARS-CoV-2</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Available">2021-08-19</date>
    <date dateType="Accepted">2021-02-19</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="doi">10.1021/acs.jproteome.0c00929</alternateIdentifier>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4552687</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4287439</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/embargoedAccess">Embargoed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The SARS-CoV-2 virus is the causative agent of the 2020 pandemic leading to the COVID-19 respiratory disease. With many scientific and humanitarian efforts ongoing to develop diagnostic tests, vaccines, and treatments for COVID-19, and to prevent the spread of SARS-CoV-2, mass spectrometry research, including proteomics, is playing a role in determining the biology of this viral infection. Proteomics studies are starting to lead to an understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein-protein interactions, and post-translational modifications. This is beginning to provide insights into potential therapeutic targets or diagnostic strategies that can be used to reduce the long-term burden of the pandemic. However, the extraordinary situation caused by the global pandemic is also highlighting the need to improve mass spectrometry data and workflow sharing. We therefore describe freely available data and computational resources that can facilitate and assist the mass spectrometry-based analysis of SARS-CoV-2. We exemplify this by reanalyzing a virus-host interactome dataset to detect protein-protein interactions and identify host proteins that could potentially be used as targets for drug repurposing.&lt;/p&gt;</description>
  </descriptions>
</resource>
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