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		<title>New Python Package Puts Biomarker Discoveries to the Test Before They Reach the Clinic</title>
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		<pubDate>Sat, 17 Oct 2026 09:35:23 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[biomarker]]></category>
		<category><![CDATA[biomarker discovery]]></category>
		<category><![CDATA[BMC Bioinformatics]]></category>
		<category><![CDATA[feature]]></category>
		<category><![CDATA[Feature Selection]]></category>
		<category><![CDATA[immunotherapy]]></category>
		<category><![CDATA[lung cancer]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[Reproducibility]]></category>
		<category><![CDATA[Robust]]></category>
		<category><![CDATA[ROOFS]]></category>
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					<description><![CDATA[A new open-source Python package called ROOFS benchmarks multiple feature selection methods on a researcher's own data, evaluating predictive performance with optimism correction, stability, robustness, and detection rates on semi-synthetic ground truth, demonstrated on the PIONeeR lung cancer immunotherapy biomarker study.]]></description>
		
		
		
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