<?xml version="1.0"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en">
	<id>https://3demmethods.i2pc.es/index.php?action=history&amp;feed=atom&amp;title=2024Jamali_Modelangelo</id>
	<title>2024Jamali Modelangelo - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://3demmethods.i2pc.es/index.php?action=history&amp;feed=atom&amp;title=2024Jamali_Modelangelo"/>
	<link rel="alternate" type="text/html" href="https://3demmethods.i2pc.es/index.php?title=2024Jamali_Modelangelo&amp;action=history"/>
	<updated>2026-05-24T21:05:56Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
	<generator>MediaWiki 1.44.2</generator>
	<entry>
		<id>https://3demmethods.i2pc.es/index.php?title=2024Jamali_Modelangelo&amp;diff=4878&amp;oldid=prev</id>
		<title>WikiSysop: Created page with &quot;== Citation ==  K. Jamali, L. Käll, R. Zhang, A. Brown, D. Kimanius, and S. H. Scheres, “Automated model building and protein identification in cryo-EM maps,” Nature, vol. 628, no. 8007, pp. 450–457, 2024.  == Abstract ==  Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learnin...&quot;</title>
		<link rel="alternate" type="text/html" href="https://3demmethods.i2pc.es/index.php?title=2024Jamali_Modelangelo&amp;diff=4878&amp;oldid=prev"/>
		<updated>2024-12-23T19:43:25Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  K. Jamali, L. Käll, R. Zhang, A. Brown, D. Kimanius, and S. H. Scheres, “Automated model building and protein identification in cryo-EM maps,” Nature, vol. 628, no. 8007, pp. 450–457, 2024.  == Abstract ==  Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learnin...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
&lt;br /&gt;
K. Jamali, L. Käll, R. Zhang, A. Brown, D. Kimanius, and S. H. Scheres, “Automated model building and protein identification in cryo-EM maps,” Nature, vol. 628, no. 8007, pp. 450–457, 2024.&lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.&lt;br /&gt;
&lt;br /&gt;
== Keywords ==&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
&lt;br /&gt;
https://www.nature.com/articles/s41586-024-07215-4&lt;br /&gt;
&lt;br /&gt;
== Related software ==&lt;br /&gt;
&lt;br /&gt;
== Related methods ==&lt;br /&gt;
&lt;br /&gt;
== Comments ==&lt;/div&gt;</summary>
		<author><name>WikiSysop</name></author>
	</entry>
</feed>