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	<title>2026Schreiber Turonova TANGO - Revision history</title>
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	<updated>2026-05-01T07:51:43Z</updated>
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		<id>https://3demmethods.i2pc.es/index.php?title=2026Schreiber_Turonova_TANGO&amp;diff=5167&amp;oldid=prev</id>
		<title>Vilas: Created page with &quot;== Citation ==  M. Schreiber, B. Turoňová,  TANGO: Analysis and curation of particles in cryo-electron tomography. Nat Commun 17, 1557 (2026).   == Abstract ==  Cryo-electron tomography (cryo-ET) enables the visualization of cellular structures in near-native environments, but its potential for spatial analysis has been underutilized due to a lack of versatile tools accommodating biological sample diversity. Available solutions often rely on case-specific or hypothesis...&quot;</title>
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		<updated>2026-02-20T12:58:36Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  M. Schreiber, B. Turoňová,  TANGO: Analysis and curation of particles in cryo-electron tomography. Nat Commun 17, 1557 (2026).   == Abstract ==  Cryo-electron tomography (cryo-ET) enables the visualization of cellular structures in near-native environments, but its potential for spatial analysis has been underutilized due to a lack of versatile tools accommodating biological sample diversity. Available solutions often rely on case-specific or hypothesis...&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;
M. Schreiber, B. Turoňová,  TANGO: Analysis and curation of particles in cryo-electron tomography. Nat Commun 17, 1557 (2026). &lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Cryo-electron tomography (cryo-ET) enables the visualization of cellular structures in near-native environments, but its potential for spatial analysis has been underutilized due to a lack of versatile tools accommodating biological sample diversity. Available solutions often rely on case-specific or hypothesis-driven approaches, while holistic analyses remain challenging. In this work, we introduce TANGO (Twist-Aware Neighborhoods for Geometric Organization), a framework leveraging point cloud descriptors to analyze spatial arrangements of particles, such as macromolecular complexes, in cryo-ET. By encoding relative positions and orientations of particles as twist vectors, TANGO enables rotationally invariant feature extraction, including structured neighborhood occupancy, lattice topology, or angular deviations. Its modular design and user-friendly interface allow for customization of features, facilitating exploratory analyses of spatial patterns in diverse experimental datasets. With its open-source Python implementation, TANGO advances the ability to decode complex cellular architectures and their functional relationships, offering a particle data analysis tool for the cryo-ET community.&lt;br /&gt;
&lt;br /&gt;
== Keywords ==&lt;br /&gt;
Cryo-electron tomography (Cryo-ET), Particle analysis, Data curation, Subtomogram averaging&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
https://doi.org/10.1038/s41467-026-69195-5&lt;/div&gt;</summary>
		<author><name>Vilas</name></author>
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