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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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                <text>Dominio científico: Coronavirus</text>
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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="21992">
              <text>Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA</text>
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          <name>Creator</name>
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            <elementText elementTextId="21993">
              <text>Rottier Peter JM, Bouwmeester Diane, Setterquist Robert A, Whitley Penn, Raaben Matthijs, de Haan Cornelis AM</text>
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          <description>An account of the resource</description>
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            <elementText elementTextId="21994">
              <text>Abstract Background Sensitivity and accuracy are key points when using microarrays to detect alterations in gene expression under different conditions. Critical to the acquisition of reliable results is the preparation of the RNA. In the field of virology, when analyzing the host cell's reaction to infection, the often high representation of viral RNA (vRNA) within total RNA preparations from infected cells is likely to interfere with microarray analysis. Yet, this effect has not been investigated despite the many reports that describe gene expression profiling of virus-infected cells using microarrays. Results In this study we used coronaviruses as a model to show that vRNA indeed interferes with microarray analysis, decreasing both sensitivity and accuracy. We also demonstrate that the removal of vRNA from total RNA samples, by means of virus-specific oligonucleotide capturing, significantly reduced the number of false-positive hits and increased the sensitivity of the method as tested on different array platforms. Conclusion We therefore recommend the specific removal of vRNA, or of any other abundant 'contaminating' RNAs, from total RNA samples to improve the quality and reliability of microarray analyses.</text>
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            <elementText elementTextId="21995">
              <text>2008</text>
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          <name>Identifier</name>
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            <elementText elementTextId="21996">
              <text>DOI: 10.1186/1471-2164-9-221</text>
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            <elementText elementTextId="21997">
              <text>BMC Genomics</text>
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            <elementText elementTextId="21998">
              <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="21999">
              <text>Genetics, Biotechnology</text>
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          <name>Language</name>
          <description>A language of the resource</description>
          <elementTextContainer>
            <elementText elementTextId="22000">
              <text>EN</text>
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