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	<title>Confidential computing in genomics &#8211; BIOENGINEER.ORG</title>
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		<title>Revolutionizing Genome Studies with SECRET-GWAS</title>
		<link>https://bioengineer.org/revolutionizing-genome-studies-with-secret-gwas/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Thu, 02 Oct 2025 20:37:10 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[confidential computing]]></category>
		<category><![CDATA[Confidential computing in genomics]]></category>
		<category><![CDATA[Diverse genomic datasets]]></category>
		<category><![CDATA[genome-wide association studies]]></category>
		<category><![CDATA[genomic diversity]]></category>
		<category><![CDATA[Population-scale genomic analysis]]></category>
		<category><![CDATA[Privacy-preserving GWAS]]></category>
		<category><![CDATA[rare disease genomics]]></category>
		<category><![CDATA[secure data collaboration]]></category>
		<category><![CDATA[Secure genomic collaboration]]></category>
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					<description><![CDATA[In the rapidly evolving field of genomics, the significance of genome-wide association studies (GWAS) cannot be overstated. However, a critical challenge that has emerged is the lack of global diversity representation in genomic data from individual institutions. This is particularly problematic when studying rare variants and diseases, where the genetic landscape can vary significantly across [&#8230;]]]></description>
		
		
		
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