WikiSysop: Created page with "== Citation == He, J. & Huang, S.-Y. EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps. Briefings in bioinformatics, 2021, bbab156 ==..."

2021-11-08T11:23:11Z

Created page with "== Citation == He, J. & Huang, S.-Y. EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps. Briefings in bioinformatics, 2021, bbab156 ==..."

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== Citation ==

He, J. & Huang, S.-Y. EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps. Briefings in bioinformatics, 2021, bbab156

== Abstract ==

Cryo-electron microscopy (cryo-EM) has become one of important experimental methods in structure determination. However, despite the rapid growth in the number of deposited cryo-EM maps motivated by advances in microscopy instruments and image processing algorithms, building accurate structure models for cryo-EM maps remains a challenge. Protein secondary structure information, which can be extracted from EM maps, is beneficial for cryo-EM structure modeling. Here, we present a novel secondary structure annotation framework for cryo-EM maps at both intermediate and high resolutions, named EMNUSS. EMNUSS adopts a three-dimensional (3D) nested U-net architecture to assign secondary structures for EM maps. Tested on three diverse datasets including simulated maps, middle resolution experimental maps, and high-resolution experimental maps, EMNUSS demonstrated its accuracy and robustness in identifying the secondary structures for cyro-EM maps of various resolutions. The EMNUSS program is freely available at http://huanglab.phys.hust.edu.cn/EMNUSS.

== Keywords ==

== Links ==

https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbab156/6265218

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== Related methods ==

== Comments ==

2021He EMNUSS - Revision history

WikiSysop: Created page with "== Citation == He, J. & Huang, S.-Y. EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps. Briefings in bioinformatics, 2021, bbab156 ==..."