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		<title>Climbing the causal ladder: a new framework sorts real cancer drug targets from statistical noise</title>
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		<category><![CDATA[causal]]></category>
		<category><![CDATA[Causal Inference]]></category>
		<category><![CDATA[Cervical cancer]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Genomics]]></category>
		<category><![CDATA[HPV]]></category>
		<category><![CDATA[integration]]></category>
		<category><![CDATA[ladder]]></category>
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		<category><![CDATA[systems biology]]></category>
		<category><![CDATA[TCGA]]></category>
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					<description><![CDATA[A new evidence-accounting framework called the Causal Integration Ladder separates statistical association from causal, therapeutically tractable mechanism in cervical cancer, applying five evidence levels to TCGA-CESC genomic data and showing that even promising candidates like CDKN2A and CDC20 lack complete causal validation.]]></description>
		
		
		
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