Journal article Open Access

COSIFER: a Python package for the consensus inference of molecular interaction networks

Manica, M.; Bunne, C.; Mathis, R.; Cadow, J.; Ahsen, M.; Stolovitzky; Martínez, M.


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  <identifier identifierType="URL">https://zenodo.org/record/4748570</identifier>
  <creators>
    <creator>
      <creatorName>Manica, M.</creatorName>
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      <affiliation>IBM Research Europe</affiliation>
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    <creator>
      <creatorName>Bunne, C.</creatorName>
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      <familyName>Bunne</familyName>
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      <creatorName>Mathis, R.</creatorName>
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      <creatorName>Cadow, J.</creatorName>
      <givenName>J.</givenName>
      <familyName>Cadow</familyName>
      <affiliation>IBM Research Europe</affiliation>
    </creator>
    <creator>
      <creatorName>Ahsen, M.</creatorName>
      <givenName>M.</givenName>
      <familyName>Ahsen</familyName>
      <affiliation>Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai</affiliation>
    </creator>
    <creator>
      <creatorName>Stolovitzky</creatorName>
      <affiliation>Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai</affiliation>
    </creator>
    <creator>
      <creatorName>Martínez, M.</creatorName>
      <givenName>M.</givenName>
      <familyName>Martínez</familyName>
      <affiliation>IBM Research Europe</affiliation>
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  <titles>
    <title>COSIFER: a Python package for the consensus inference of molecular interaction networks</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-11-02</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4748570</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1093/bioinformatics/btaa942</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/ipc</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/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The advent of high-throughput technologies has provided researchers with measurements of thousands of molecular entities and enable the investigation of the internal regulatory apparatus of the cell. However, network inference from high-throughput data is far from being a solved problem. While a plethora of different inference methods have been proposed, they often lead to non-overlapping predictions, and many of them lack user-friendly implementations to enable their broad utilization. Here, we present Consensus Interaction Network Inference Service (COSIFER), a package and a companion web-based platform to infer molecular networks from expression data using state-of-the-art consensus approaches. COSIFER includes a selection of state-of-the-art methodologies for network inference and different consensus strategies to integrate the predictions of individual methods and generate robust networks.&lt;br&gt;
&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/826121/">826121</awardNumber>
      <awardTitle>individualizedPaediatricCure: Cloud-based virtual-patient models for precision paediatric oncology</awardTitle>
    </fundingReference>
  </fundingReferences>
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