WikiSysop: Created page with "== Citation == Y.-T. Liu, H. Fan, J. J. Hu, and Z. H. Zhou, “Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning,” Nature methods, vol. 22, pp. 113–123, 2025. == Abstract == While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the ‘preferred’ orientation problem) remains a complication for most specimens. Existing..."

2025-02-19T07:43:34Z

Created page with "== Citation == Y.-T. Liu, H. Fan, J. J. Hu, and Z. H. Zhou, “Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning,” Nature methods, vol. 22, pp. 113–123, 2025. == Abstract == While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the ‘preferred’ orientation problem) remains a complication for most specimens. Existing..."

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== Citation ==

Y.-T. Liu, H. Fan, J. J. Hu, and Z. H. Zhou, “Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning,” Nature methods, vol. 22, pp. 113–123, 2025.

== Abstract ==

While advances in single-particle cryo-EM have enabled the structural
determination of macromolecular complexes at atomic resolution,
particle orientation bias (the ‘preferred’ orientation problem) remains
a complication for most specimens. Existing solutions have relied on
biochemical and physical strategies applied to the specimen and are
often complex and challenging. Here, we develop spIsoNet, an end-to-end
self-supervised deep learning-based software to address map anisotropy
and particle misalignment caused by the preferred-orientation problem.
Using preferred-orientation views to recover molecular information in
under-sampled views, spIsoNet improves both angular isotropy and particle
alignment accuracy during 3D reconstruction. We demonstrate spIsoNet’s
ability to generate near-isotropic reconstructions from representative
biological systems with limited views, including ribosomes, β-galactosidases
and a previously intractable hemagglutinin trimer dataset. spIsoNet can
also be generalized to improve map isotropy and particle alignment of
preferentially oriented molecules in subtomogram averaging. Therefore,
without additional specimen-preparation procedures, spIsoNet provides a
general computational solution to the preferred-orientation problem.

== Keywords ==

== Links ==

https://www.nature.com/articles/s41592-024-02505-1

== Related software ==

== Related methods ==

== Comments ==

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