1 Ocak 2020 Dergi makalesi Açık Erişim

Unsal, Serbulent; Acar, Aybar; Itik, Mehmet; Kabatas, Ayse; Gedikli, Oznur; Ozdemir, Feyyaz; Turhan, Kemal

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/5929</identifier>
  <creators>
    <creator>
      <creatorName>Unsal, Serbulent</creatorName>
      <givenName>Serbulent</givenName>
      <familyName>Unsal</familyName>
      <affiliation>Karadeniz Tech Univ, Biostat &amp; Med Informat, Trabzon, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Acar, Aybar</creatorName>
      <givenName>Aybar</givenName>
      <familyName>Acar</familyName>
      <affiliation>Middle East Tech Univ, Canc Syst Biol Lab, Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Itik, Mehmet</creatorName>
      <givenName>Mehmet</givenName>
      <familyName>Itik</familyName>
      <affiliation>Izmir Democracy Univ, Mech Engn, Izmir, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Kabatas, Ayse</creatorName>
      <givenName>Ayse</givenName>
      <familyName>Kabatas</familyName>
      <affiliation>Karadeniz Tech Univ, Trabzon, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Gedikli, Oznur</creatorName>
      <givenName>Oznur</givenName>
      <familyName>Gedikli</familyName>
      <affiliation>Karadeniz Tech Univ, Physiol, Trabzon, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Ozdemir, Feyyaz</creatorName>
      <givenName>Feyyaz</givenName>
      <familyName>Ozdemir</familyName>
      <affiliation>Karadeniz Tech Univ, Med Oncol, Trabzon, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Turhan, Kemal</creatorName>
      <givenName>Kemal</givenName>
      <familyName>Turhan</familyName>
      <affiliation>Karadeniz Tech Univ, Biostat &amp; Med Informat, Trabzon, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Personalized Tumor Growth Prediction Using Multiscale Modeling</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/5929</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.30621/jbachs.2020.1245</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Purpose: Cancer is one of the most complex phenomena in biology and medicine. Extensive attempts have been made to work around this complexity. In this study, we try to take a selective approach; not modeling each particular facet in detail but rather only the pertinent and essential parts of the tumor system are simulated and followed by optimization, revealing specific traits. This leads us to a pellucid personalized model which is noteworthy as it closely approximates existing experimental results.</description>
  </descriptions>
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