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		<title>Revolutionizing Disease Understanding: New Algorithm Connects Social and Biological Networks to Identify Key Proteins in Human Health</title>
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		<pubDate>Tue, 08 Apr 2025 17:42:49 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Disease Mechanism Algorithms]]></category>
		<category><![CDATA[Interdisciplinary Bioinformatics Research]]></category>
		<category><![CDATA[Protein Interaction Anomaly Detection]]></category>
		<category><![CDATA[Social Network Analysis in Biology]]></category>
		<category><![CDATA[Targeted Therapy Development]]></category>
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					<description><![CDATA[In a remarkable development that bridges the fields of bioinformatics and machine learning, researchers at Ben-Gurion University of the Negev have unveiled a powerful new algorithm that has the potential to revolutionize our understanding of human biology and the intricacies of disease. This innovative machine-learning technique, known as Weighted Graph Anomalous Node Detection (WGAND), draws [&#8230;]]]></description>
		
		
		
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