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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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              <text>A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome</text>
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          <name>Creator</name>
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              <text>Md. Zakir Hossain, Rozina Akter, Md Mahmudul Hasan, Md. Shahin Ullah, Md. Jaynul Abedin, G. M. Ahsan Ullah</text>
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              <text>The new epidemic Middle East Respiratory Syndrome (MERS) is caused by a type of human coronavirus called MERS-CoV which has global fatality rate of about 30%. We are investigating potential antiviral therapeutics against MERS-CoV by using host microRNAs (miRNAs) which may downregulate viral gene expression to quell viral replication. We computationally predicted potential 13 cellular miRNAs from 11 potential hairpin sequences of MERS-CoV genome. Our study provided an interesting hypothesis that those miRNAs, that is, hsa-miR-628-5p, hsa-miR-6804-3p, hsa-miR-4289, hsa-miR-208a-3p, hsa-miR-510-3p, hsa-miR-18a-3p, hsa-miR-329-3p, hsa-miR-548ax, hsa-miR-3934-5p, hsa-miR-4474-5p, hsa-miR-7974, hsa-miR-6865-5p, and hsa-miR-342-3p, would be antiviral therapeutics against MERS-CoV infection.</text>
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              <text>2014</text>
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          <name>Identifier</name>
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              <text>DOI: 10.1155/2014/967946</text>
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          <name>Source</name>
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              <text>Advances in Bioinformatics</text>
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          <name>Publisher</name>
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              <text>Hindawi Limited</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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              <text>Biology (General), Statistics</text>
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