https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2025Chen_GMMs2025Chen GMMs - Revision history2026-05-24T21:06:54ZRevision history for this page on the wikiMediaWiki 1.44.2https://3demmethods.i2pc.es/index.php?title=2025Chen_GMMs&diff=4999&oldid=prevWikiSysop: Created page with "== Citation == M. Chen, “Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks,” Communications Biology, vol. 8, no. 1, pp. 1–9, 2025. == Abstract == Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially w..."2025-06-20T10:37:34Z<p>Created page with "== Citation == M. Chen, “Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks,” Communications Biology, vol. 8, no. 1, pp. 1–9, 2025. == Abstract == Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially w..."</p>
<p><b>New page</b></p><div>== Citation ==<br />
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M. Chen, “Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks,” Communications Biology, vol. 8, no. 1, pp. 1–9, 2025.<br />
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== Abstract ==<br />
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Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic<br />
resolution. However, building molecular models with good stereochemical geometry from those<br />
structures can be challenging and time-consuming, especially when many structures are obtained<br />
from datasets with conformational heterogeneity. Here we present a model refinement protocol that<br />
automatically generates series of molecular models from CryoEM datasets, which describe the<br />
dynamics of the macromolecular systemand have near-perfect geometry scores. This method makes<br />
it easier to interpret the movement of the protein complex fromheterogeneity analysis and to compare<br />
the structural dynamics observed from CryoEM data with results from other experimental and<br />
simulation techniques.<br />
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== Keywords ==<br />
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== Links ==<br />
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https://www.nature.com/articles/s42003-025-08202-9<br />
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== Related software ==<br />
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== Related methods ==<br />
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== Comments ==</div>WikiSysop