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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Network building with Cytoscape App queries to the BioGateway 3.0 triple store</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Stian Holmås Vladimir Mironov Martin Kuiper</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Norwegian University of Science and Technology, NTNU</institution>
        </aff>
      </contrib-group>
      <abstract>
        <p>We have developed the BioGateway App, a Cytoscape plugin that supports the building of a wish list of questions that are translated to SPARQL queries, which are launched against the BioGateway server. We demonstrate the functionality of the BioGateway App both in simple and more complex use cases, taken from our website https://www.biogateway.eu/examples/</p>
      </abstract>
      <kwd-group>
        <kwd>triple store</kwd>
        <kwd>cytoscape app</kwd>
        <kwd>network building</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>1.1.</p>
      <p>Introduction</p>
    </sec>
    <sec id="sec-2">
      <title>The BioGateway triple store</title>
      <p>
        The BioGateway (BGW) triple store [
        <xref ref-type="bibr" rid="ref1 ref2">1, 2</xref>
        ] was one of the first major RDF resources
available with biological information. The use of SPARQL to query triple stores proved
to be one of the major limiting factors for the wider acceptance of the Semantic Web
technologies by systems biologists. Therefore, we now reach out to the relatively large
user community of the biological network analysis platform Cytoscape through the
development of the BioGateway App plugin.
1.2.
      </p>
    </sec>
    <sec id="sec-3">
      <title>The BioGateway Cytoscape App</title>
      <p>
        The main feature of the BioGateway App is the Query Builder, which supports the
design of queries that are built from definitions of proteins or genes and a relationship
to either an ontology term or another protein or gene. By adding additional query parts
line by line, increasingly complex and restrictive or inclusive queries can be composed.
The Run Query command converts these to native SPARQL queries that are launched
against the BioGateway 3.0 SPARQL endpoint [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ].
1.3.
      </p>
    </sec>
    <sec id="sec-4">
      <title>The biological data in the store</title>
      <p>
        The main information that is subject to the query is obtained from IntAct [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ],
UniProtKB [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] and the Gene Ontology database [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. To allow a user a special focus on
gene regulation we also included several resources with regulatory relations of
transcription factors and their target genes.
      </p>
      <p>Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
The selection of terms of interest such as genes, proteins, ontology terms and relation
types is facilitated by an autocomplete function that is driven by a REST API of a
NoSQL database loaded with all the entity names and metadata from the BioGateway
server, to allow quick response times. To ensure compatibility between the App and the
BioGateway data, upon startup the App fetches an XML-based configuration file from
our webserver. This file contains the relation types and their URIs, default settings and
the default layout style for BioGateway graphs, as well as available metadata types and
the query constraints that this metadata enables, allowing some updates to the App
without requiring the user to reinstall it. User preferences set in the BioGateway tab of
the Cytoscape Control Panel are stored between sessions, such as the default query
constraints related to species, data sources, and additional selection criteria for querying
the BioGateway content.
2.2.</p>
    </sec>
    <sec id="sec-5">
      <title>Query constraints</title>
      <p>Next to specifying the results through the definition of restrictive queries, the Query
Constraints section of the BioGateway tab in the Control Panel allows additional
constraints for specific relations, such as setting a minimum confidence score for
ProteinProtein Interactions, as provided by IntAct (Orchard et al. 2013). This control panel
also allows the selection of extra types of metadata to be loaded together with the
results, but as this may significantly increase query time, this metadata can also be added
after the network is complete (Reload Metadata), so that it can be used for filtering and
display options.
3.</p>
    </sec>
    <sec id="sec-6">
      <title>Scope of the demo</title>
      <p>We will demonstrate the functionality of the BioGateway App both in simple and more
complex use cases, taken from https://www.biogateway.eu/examples/. While BGW
3.0.0 contains only human data, BGW 3.0.1 (release date expected in December 2019)
will include data for 25 best-studied eukaryotes.
4.</p>
    </sec>
  </body>
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