February 4, 2017 Software Open Access

Daniel Himmelstein

DataCite XML Export

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  <identifier identifierType="DOI">10.5281/zenodo.268654</identifier>
  <creators>
    <creator>
      <creatorName>Daniel Himmelstein</creatorName>
    </creator>
  </creators>
  <titles>
    <title>dhimmel/learn v1.0: the machine learning repository for Project Rephetio</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <subjects>
    <subject>rephetio</subject>
    <subject>machine learning</subject>
    <subject>hetnet edge prediction</subject>
    <subject>drug repurposing</subject>
    <subject>Rephetio</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2017-02-04</date>
  </dates>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/268654</alternateIdentifier>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementTo">https://github.com/dhimmel/learn/tree/v1.0.0</relatedIdentifier>
  </relatedIdentifiers>
  <version>v1.0.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons Zero v1.0 Universal</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Project Rephetio is an open project to systematically repurpose drugs. This release contains the machine learning code and data for Project Rephetio. For more information on Project Rephetio, see https://thinklab.com/p/rephetio and https://doi.org/10.1101/087619.&lt;/p&gt;</description>
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