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        <article-title>Goal-Oriented Task Composition for Bioinformatics</article-title>
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      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Karen Sutherland</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Albert Burger</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
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        <aff id="aff0">
          <label>0</label>
          <institution>Heriot-Watt University</institution>
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          <addr-line>Edinburgh</addr-line>
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        <aff id="aff1">
          <label>1</label>
          <institution>MRC</institution>
          ,
          <addr-line>Edinburgh</addr-line>
        </aff>
      </contrib-group>
      <abstract>
        <p>A key application area of semantic technologies is the fast-developing eld of bioinformatics. However, a gap exists between the computer literacy of biologists using bioinformatics tools and the computer scientists developing them. Tools such as Taverna1 provide a graphical user interface for creating biological work ows using web services and semantic technologies. However, these tools are aimed primarily at bioinformaticists, i.e. those who have an interest in biology, but are also fairly knowledgeable in computing. The level of technical detail required is generally beyond that possessed by most biologists. The work illustrated in this poster aims to bring the biologist closer to being able to create and run their own work ows by using principles from Hierarchical Task Network (HTN) planning and plan recognition. The aim is to identify the goals or questions in which a researcher may be interested, and show how these goals can be broken down into simple tasks which the computer can subsequently run.</p>
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