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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>Title</name>
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              <text>Large-scale analysis of antigenic diversity of T-cell epitopes in dengue virus</text>
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          <name>Creator</name>
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              <text>Srinivasan KN, Lee Kenneth X, Heiny AT, Khan Asif M, Tan Tin, August J Thomas, Brusic Vladimir</text>
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              <text>Abstract Background Antigenic diversity in dengue virus strains has been studied, but large-scale and detailed systematic analyses have not been reported. In this study, we report a bioinformatics method for analyzing viral antigenic diversity in the context of T-cell mediated immune responses. We applied this method to study the relationship between short-peptide antigenic diversity and protein sequence diversity of dengue virus. We also studied the effects of sequence determinants on viral antigenic diversity. Short peptides, principally 9-mers were studied because they represent the predominant length of binding cores of T-cell epitopes, which are important for formulation of vaccines. Results Our analysis showed that the number of unique protein sequences required to represent complete antigenic diversity of short peptides in dengue virus is significantly smaller than that required to represent complete protein sequence diversity. Short-peptide antigenic diversity shows an asymptotic relationship to the number of unique protein sequences, indicating that for large sequence sets (~200) the addition of new protein sequences has marginal effect to increasing antigenic diversity. A near-linear relationship was observed between the extent of antigenic diversity and the length of protein sequences, suggesting that, for the practical purpose of vaccine development, antigenic diversity of short peptides from dengue virus can be represented by short regions of sequences (~</text>
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          <name>Date</name>
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              <text>2006</text>
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          <name>Identifier</name>
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              <text>DOI: 10.1186/1471-2105-7-S5-S4</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="21204">
              <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="21206">
              <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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            <elementText elementTextId="21207">
              <text>EN</text>
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