Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps
Tao Li,
Hong Cao,
Jiahua He and
Sheng-You Huang ()
Additional contact information
Tao Li: Huazhong University of Science and Technology
Hong Cao: Huazhong University of Science and Technology
Jiahua He: Huazhong University of Science and Technology
Sheng-You Huang: Huazhong University of Science and Technology
Nature Communications, 2024, vol. 15, issue 1, 1-13
Abstract:
Abstract Cryo-electron microscopy (cryo-EM) is one of the most powerful experimental methods for macromolecular structure determination. However, accurate DNA/RNA structure modeling from cryo-EM maps is still challenging especially for protein-DNA/RNA or multi-chain DNA/RNA complexes. Here we propose a deep learning-based method for accurate de novo structure determination of DNA/RNA from cryo-EM maps at
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/s41467-024-53721-4 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53721-4
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-024-53721-4
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().