Poster Open Access

PIMKL: Pathway Induced Multiple Kernel Learning

Manica Matteo; Cadow Joris; Mathis Roland; Rodriguez Martinez Maria


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Manica Matteo</dc:creator>
  <dc:creator>Cadow Joris</dc:creator>
  <dc:creator>Mathis Roland</dc:creator>
  <dc:creator>Rodriguez Martinez Maria</dc:creator>
  <dc:date>2019-08-22</dc:date>
  <dc:description>What

• Accurate phenotype classification
• Biological interpretability
• Robustness to noise
• Handling curse of dimensionality

How

Exploit prior knowledge from biological
networks
• Apply multiple kernel learning for
feature encoding
• Use pathway annotations to enable
interpretability</dc:description>
  <dc:identifier>https://zenodo.org/record/3374413</dc:identifier>
  <dc:identifier>10.5281/zenodo.3374413</dc:identifier>
  <dc:identifier>oai:zenodo.org:3374413</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/668858/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3374412</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/ipc</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/precise</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>multiple kernel learning</dc:subject>
  <dc:title>PIMKL: Pathway Induced Multiple Kernel Learning</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePoster</dc:type>
  <dc:type>poster</dc:type>
</oai_dc:dc>
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