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		<title>Generative AI moves crop breeding from natural selection to molecular design</title>
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		<pubDate>Tue, 27 Oct 2026 00:31:51 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[AI virtual cells]]></category>
		<category><![CDATA[Breeding 5.0]]></category>
		<category><![CDATA[CRISPR-Cas]]></category>
		<category><![CDATA[crop breeding]]></category>
		<category><![CDATA[DESIGN framework]]></category>
		<category><![CDATA[Diffusion models]]></category>
		<category><![CDATA[gene regulatory elements]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[natural]]></category>
		<category><![CDATA[Protein Engineering]]></category>
		<category><![CDATA[Science China Life Sciences]]></category>
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					<description><![CDATA[A review by researchers at China Agricultural University outlines how generative AI architectures and a proposed DESIGN framework could shift crop improvement from selecting existing variants to designing novel sequences, proteins, and regulatory elements.]]></description>
		
		
		
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