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	<title>machine learning in synthetic biology &#8211; BIOENGINEER.ORG</title>
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		<title>LDBT: Machine Learning Meets Rapid Cell-Free Testing</title>
		<link>https://bioengineer.org/ldbt-machine-learning-meets-rapid-cell-free-testing/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Wed, 05 Nov 2025 17:03:54 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[accelerated genetic engineering]]></category>
		<category><![CDATA[computational biology integration]]></category>
		<category><![CDATA[DBTL cycle optimization]]></category>
		<category><![CDATA[machine learning in synthetic biology]]></category>
		<category><![CDATA[rapid cell-free testing]]></category>
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					<description><![CDATA[In the rapidly evolving landscape of synthetic biology, the quest for accelerating the design-build-test-learn (DBTL) cycle has been a cornerstone of innovation. Researchers have tirelessly sought methodologies that can streamline this iterative process, which traditionally involves designing genetic constructs, building them within biological systems, testing the outcomes, and learning from these results to inform subsequent [&#8230;]]]></description>
		
		
		
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