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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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            <description>An account of the resource</description>
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                <text>Dominio científico: Coronavirus</text>
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    <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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      <name>Dublin Core</name>
      <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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        <element elementId="50">
          <name>Title</name>
          <description>A name given to the resource</description>
          <elementTextContainer>
            <elementText elementTextId="21094">
              <text>Readjoiner: a fast and memory efficient string graph-based sequence assembler</text>
            </elementText>
          </elementTextContainer>
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        <element elementId="39">
          <name>Creator</name>
          <description>An entity primarily responsible for making the resource</description>
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              <text>Gonnella Giorgio, Kurtz Stefan</text>
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          <name>Description</name>
          <description>An account of the resource</description>
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              <text>Abstract Background Ongoing improvements in throughput of the next-generation sequencing technologies challenge the current generation of de novo sequence assemblers. Most recent sequence assemblers are based on the construction of a de Bruijn graph. An alternative framework of growing interest is the assembly string graph, not necessitating a division of the reads into k-mers, but requiring fast algorithms for the computation of suffix-prefix matches among all pairs of reads. Results Here we present efficient methods for the construction of a string graph from a set of sequencing reads. Our approach employs suffix sorting and scanning methods to compute suffix-prefix matches. Transitive edges are recognized and eliminated early in the process and the graph is efficiently constructed including irreducible edges only. Conclusions Our suffix-prefix match determination and string graph construction algorithms have been implemented in the software package Readjoiner. Comparison with existing string graph-based assemblers shows that Readjoiner is faster and more space efficient. Readjoiner is available at http://www.zbh.uni-hamburg.de/readjoiner.</text>
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              <text>2012</text>
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          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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              <text>DOI: 10.1186/1471-2105-13-82</text>
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          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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            <elementText elementTextId="21099">
              <text>BMC Bioinformatics</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>BMC</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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            <elementText elementTextId="21101">
              <text>Biology (General), Computer applications to medicine. Medical informatics</text>
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          <name>Language</name>
          <description>A language of the resource</description>
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              <text>EN</text>
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