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        <identifier>oai:figshare.com:article/32637846</identifier>
        <datestamp>2026-10-01T16:48:27Z</datestamp>
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          <dc:title>Bioinformatic and genomic analyses to identify mitochondrial genomic features associated with chronic kidney disease</dc:title>
          <dc:creator>Ruaidhrí Cappa (24167859)</dc:creator>
          <dc:subject>PUREID: 512991547</dc:subject>
          <dc:subject>Chronic kidney disease</dc:subject>
          <dc:subject>renal disease</dc:subject>
          <dc:subject>GWAS</dc:subject>
          <dc:subject>EWAS</dc:subject>
          <dc:subject>mitochondrial genomics</dc:subject>
          <dc:subject>bioinformatics</dc:subject>
          <dc:subject>statistics</dc:subject>
          <dc:description>Chronic kidney disease (CKD) is responsible for considerable morbidity and mortality and lacks a specific treatment. Research has indicated CKD has a strong heritable component, but this is not fully understood. The kidneys are dependent upon aerobic respiration which occurs in the mitochondria; therefore, it is possible that mitochondrial genomic variants could result in renal dysfunction. This project aims to identify genomic features associated with CKD, and also to assess the computational tools currently available for use in such studies and to develop new computational tools.&lt;br&gt;&lt;br&gt;</dc:description>
          <dc:date>2026-10-01T16:48:27Z</dc:date>
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