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      <title-group>
        <article-title>The Cell Cycle Ontology: an application ontology supporting the Life Sciences</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Erick Antezana</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mikel Egan~a</string-name>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ward Blonde</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Robert Stevens</string-name>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Bernard De Baets</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Vladimir Mironov</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Martin Kuiper</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Dept. of Applied Mathematics, Biometrics and Process Control, Ghent University</institution>
          ,
          <addr-line>Gent</addr-line>
          ,
          <country country="BE">Belgium</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Dept. of Biology, Norwegian University of Science and Technology</institution>
          ,
          <country country="NO">Norway</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Dept. of Molecular Genetics, Ghent University</institution>
          ,
          <addr-line>Gent</addr-line>
          ,
          <country country="BE">Belgium</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Dept. of Plant Systems Biology</institution>
          ,
          <addr-line>VIB, Gent</addr-line>
          ,
          <country country="BE">Belgium</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>School of Computer Science, The University of Manchester</institution>
          ,
          <country country="UK">UK</country>
        </aff>
      </contrib-group>
      <abstract>
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      </abstract>
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      <p>The terms and relationships provided by existing bio-ontologies only capture a
small part of our biological understanding, thus the potential of applying
computational analysis on such information remains limited. The Cell Cycle Ontology
(CCO) is designed to capture detailed information of the cell cycle process by
combining representations from several sources. CCO is an application ontology
that is supplied as an integrated turnkey system for exploratory analysis,
advanced querying, and automated reasoning. CCO supports four model organisms
(Human, Arabidopsis, Baker's yeast and Fission yeast) with separate ontologies
but also one integrated ontology. CCO holds more that 65000 concepts and more
than 20 types of relationships. CCO comprises data from existing resources such
as the Gene Ontology (GO), the Relations Ontology (RO), the IntAct database
(MI), the NCBI taxonomy, the UniProt knowledge base as well as orthology data.
An automatic pipeline builds CCO from scratch periodically: initially some
existing ontologies (GO, RO, MI, in-house ones) are automatically fetched, integrated
and merged, producing in turn a core cell cycle ontology. Then, organism-speci c
protein and gene data are added from UniProt and from the GO Annotation les,
generating four organism-speci c ontologies. Those four ontologies are merged
and more terms are included from an ontology built automatically from the
OrthoMCL execution on the cell cycle proteins. Finally, during the maintenance
phase, a semantic improvement on the OWL version is carried out: ontology
design patterns are included using the Ontology Pre-Processor Language. The
resulting CCO is designed to provide a richer view of the cell cycle regulatory
process, in particular by accommodating the intrinsic dynamics of this process.
CCO is available in: OBOF, RDF, XML, OWL, GML, and DOT. A SPARQL
endpoint allows building complex queries, such as \get the cell cycle related
proteins in A. thaliana participating in the same interaction but having di
erent locations". Visual exploration can be done via the BioPortal, the Ontology
Lookup Service, the Ontology Online service, or the DIAMONDS platform.</p>
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