<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Machine learning in genomics &#8211; BIOENGINEER.ORG</title>
	<atom:link href="https://bioengineer.org/tag/machine-learning-in-genomics/feed/" rel="self" type="application/rss+xml" />
	<link>https://bioengineer.org</link>
	<description>Bioengineering</description>
	<lastBuildDate>Mon, 26 Jan 2026 08:25:07 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.9.4</generator>

<image>
	<url>https://bioengineer.org/wp-content/uploads/2019/09/cropped-bioengineering-32x32.png</url>
	<title>Machine learning in genomics &#8211; BIOENGINEER.ORG</title>
	<link>https://bioengineer.org</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">72741379</site>	<item>
		<title>Streamlining ACMG Variant Classifications with BIAS-2015</title>
		<link>https://bioengineer.org/streamlining-acmg-variant-classifications-with-bias-2015/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 26 Jan 2026 08:24:43 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[automated classification]]></category>
		<category><![CDATA[Based on the content]]></category>
		<category><![CDATA[BIAS-2015 algorithm]]></category>
		<category><![CDATA[eRepo dataset** **Açıklama:** 1. **ACMG variant classifications:** Makalenin temel konusu ACMG kılavuzlarına göre varyant sınıflandırmasıdır. 2. **BIAS-2015 algorithm:** Araştırmanın oda]]></category>
		<category><![CDATA[Genetic diagnostics]]></category>
		<category><![CDATA[here are 5 appropriate tags: **ACMG variant classifications]]></category>
		<category><![CDATA[İçeriğe uygun 5 etiket: **ACMG variant classifications]]></category>
		<category><![CDATA[Machine learning in genomics]]></category>
		<guid isPermaLink="false">https://bioengineer.org/streamlining-acmg-variant-classifications-with-bias-2015/</guid>

					<description><![CDATA[In an era marked by rapid advancements in genomic medicine, the automating of variant classifications has emerged as a crucial topic of exploration. The recent study led by Eisenhart, Brickey, and Nadon sheds significant light on this area by utilizing a novel tool, BIAS-2015 v2.1.1. This innovative algorithm aims to streamline the complexities surrounding the [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">320976</post-id>	</item>
		<item>
		<title>Exploring Archaeal Promoters with Explainable CNN Models</title>
		<link>https://bioengineer.org/exploring-archaeal-promoters-with-explainable-cnn-models/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sun, 26 Oct 2025 02:52:43 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Archaeal promoters]]></category>
		<category><![CDATA[convolutional neural networks]]></category>
		<category><![CDATA[Explainable AI in genomics]]></category>
		<category><![CDATA[Machine learning in genomics]]></category>
		<category><![CDATA[Transcriptional control in Archaea]]></category>
		<guid isPermaLink="false">https://bioengineer.org/exploring-archaeal-promoters-with-explainable-cnn-models/</guid>

					<description><![CDATA[In a groundbreaking study published in BMC Genomics, researchers Mohammed Shujaat and S. Q. Mao presented an innovative approach to characterizing archaeal promoters by leveraging cutting-edge explainable artificial intelligence techniques. This research marks a significant milestone in genomics, shedding light on the complexities of archaeal gene regulation. The ability to decipher the underlying mechanisms of [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">286925</post-id>	</item>
	</channel>
</rss>
