EMPIAR-11811 - Structural and functional insights into the enzymatic plasticity of the SARS-CoV-2 NiRAN domain [19338 multi-frame micrographs composed of 50 frames each in TIFF format]

EMPIAR-11811

Structural and functional insights into the enzymatic plasticity of the SARS-CoV-2 NiRAN domain [19338 multi-frame micrographs composed of 50 frames each in TIFF format]

Publication:

Structural and functional insights into the enzymatic plasticity of the SARS-CoV-2 NiRAN domain

Campbell EA, Small GI, Darst SA

Molecular Cell 83 (2023) 3921-3930

PMID: 37890482

DOI: 10.1016/j.molcel.2023.10.001

Related EMDB entry:

EMD-40707 EMD-40708

Deposited:

2023-11-28

Released:

2025-07-12

Last modified:

2025-07-12

Imageset size:

5.39 TB

Imageset DOI:

10.6019/EMPIAR-11811

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multiframe micrographs

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

19338

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(None, None)

Details:

Multiframe micrographs in TIFF format that were used as the basis for processing and determining a cryo-EM maps for the GDP-cap-i structure (EMD-40708, PDB-8SQK) and 20mer-SL structure (EMD-40707, PDB-8SQJ).

Files:

このエントリはPDBjからダウンロードすることはできません。

選択したファイルを無圧縮zipファイルにアーカイブ化してダウンロードします。

ダウンロードするファイル数やサイズによっては、膨大な時間がかかります。また、この機能は不安定で正常に動作しない可能性があり、ダウンロードされたファイルのチェックサムは検証されません。

rsync、aspera、globus 等の利用をおすすめします。

選択したファイルのリストをダウンロードします。

rsyncコマンド等でファイルリストを指定してダウンロードすることが可能です。

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

Browse All Files

Quick Links

Browse EMPIAR

Sample Preparation Widget

Volume Browser

Tomo Viewer Prototype

Claim entries to your ORCiD

Talks and Tutorials

EMPIAR Quick tour

Publications

Re-use study

Statistics

EMPIAR in the news

COVID-19 Data Portal

EMDB

BioImage Archive

PDBe

EMNavigator@PDBj

PDBj

Citations

prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.

He L, Bartesaghi A. (2026)

CryoSIP: unleashing protein high-resolution Cryo-EM via semantic-instance collaborative picking.

Deng Y, Wang S, Xiang M, Li Y, Zhuo L, Cao D, Fu X, Zou Q. (2026)

Chart builder: an interactive tool for user driven data visualization in the electron microscopy data bank.

Fonseca N, Duraisamy AK, Wang Z, Somasundharam S, Tayebinia M, de Oliveira LC, Ma M, Turner J, Patwardhan A, Kleywegt GJ, Hartley M, Morris KL. (2026)

CryoVirusDB: An Annotated Dataset for AI-Based Virus Particle Identification in Cryo-EM Micrographs.

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements.

Jones HN, Deshmukh A, Pande K. (2026)

CryoGS: High-Quality Cryo-EM Homogeneous Reconstruction by Gaussian Splatting

Zeng B, Liu S, Cheng S, Xu G, Fan H. (2026)

Point cloud deformation modeling for particle selection following cryo-EM 2D classification.

Wang X, Mo Z, Li F, Zhang F, Wan X. (2026)

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Kishore V, Debarnot V, Righetto RD, Engel BD, Dokmanić I. (2026)

CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.

Schäfer JH, Calza A, Hom K, Damodar P, Peng R, Bogdanović N, Lander GC, Stagg SM, Cianfrocco MA. (2025)