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		<title>iReceptor Plus partners published a review article on mining AIRRs for biological and clinical information using machine learning</title>
		<link>https://www.ireceptor-plus.com/ireceptor-plus-partners-published-a-review-article-on-mining-airrs-for-biological-and-clinical-information-using-machine-learning/</link>
		
		<dc:creator><![CDATA[Boaz Babai]]></dc:creator>
		<pubDate>Tue, 26 Jan 2021 10:30:13 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[AIRRs]]></category>
		<category><![CDATA[biosensors]]></category>
		<category><![CDATA[Gur Yaari]]></category>
		<category><![CDATA[Lindsay Cowell]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Victor Greiff]]></category>
		<guid isPermaLink="false">https://www.ireceptor-plus.com/?p=1964</guid>

					<description><![CDATA[<p>Research entitled “Mining adaptive immune receptor repertoires for biological and clinical information using machine learning” has been published in the journal Current Opinion in Systems Biology by three iR+ partners.</p>
<p>The post <a href="https://www.ireceptor-plus.com/ireceptor-plus-partners-published-a-review-article-on-mining-airrs-for-biological-and-clinical-information-using-machine-learning/">iReceptor Plus partners published a review article on mining AIRRs for biological and clinical information using machine learning</a> appeared first on <a href="https://www.ireceptor-plus.com">iReceptor Plus</a>.</p>
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