Cryo‐EM map interpretation and protein model‐building using iterative map segmentation-Reference-Cited by-同舟云学术

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Cryo‐EM map interpretation and protein model‐building using iterative map segmentation

Published:2019-10-24 Issue:1 Volume:29 Page:87-99
ISSN:0961-8368
Container-title:Protein Science
language:en
Short-container-title:Protein Science

Author:

Terwilliger Thomas C.¹²^ORCID,Adams Paul D.³⁴,Afonine Pavel V.³,Sobolev Oleg V.³

Affiliation:

1. Los Alamos National Laboratory Los Alamos New Mexico

2. New Mexico Consortium Los Alamos New Mexico

3. Molecular Biophysics & Integrated Bioimaging Division Lawrence Berkeley National Laboratory Berkeley California

4. Department of Bioengineering University of California Berkeley Berkeley California

Funder

Lawrence Berkeley National Laboratory

U.S. Department of Energy

National Institutes of Health

Publisher

Wiley

Subject

Molecular Biology,Biochemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pro.3740

Reference48 articles.

1. How Good Can Single-Particle Cryo-EM Become? What Remains Before It Approaches Its Physical Limits?

2. The development of cryo-EM into a mainstream structural biology technique

3. The Resolution Revolution

4. Overview and future of single particle electron cryomicroscopy

5. The Protein Data Bank

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. All-atom RNA structure determination from cryo-EM maps;Nature Biotechnology;2024-02-23

2. Deep Learning Approach to Identify Protein’s Secondary Structure Elements;Lecture Notes in Computer Science;2024

3. Improvement of cryo-EM maps by simultaneous local and non-local deep learning;Nature Communications;2023-06-03

4. Automatic and accurate ligand structure determination guided by cryo-electron microscopy maps;Nature Communications;2023-03-01

5. Improved AlphaFold modeling with implicit experimental information;Nature Methods;2022-10-20

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