EMPIAR-11065 - Nudaurelia capensis omega virus procapsid at pH7.6 (insect cell expressed VLPs) [multiple data sets in MRC format]

EMPIAR-11065

Nudaurelia capensis omega virus procapsid at pH7.6 (insect cell expressed VLPs) [multiple data sets in MRC format]

Publication:

Unraveling the maturation pathway of a eukaryotic virus through cryo-EM

Castells-Graells R, Hesketh EL, Matsui T, Johnson JE, Ranson NA, Lawson DM, Lomonossoff GP

Proceedings of the National Academy of Sciences of the United States of America 123 (2026)

PMID: 41739563

DOI: 10.1073/pnas.2420493123

Related EMDB entry:

EMD-15134

Deposited:

2022-06-13

Released:

2023-02-14

Last modified:

2026-04-07

Imageset size:

6.39 TB

Imageset DOI:

10.6019/EMPIAR-11065

Experimental metadata:

Download xml json

Compressed by PDBj:

Image formats and pixel types shown below are those of the original, non-compressed files.

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Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. unaligned movies

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

6926

Image size:

(4096, 4096)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(1.065, 1.065)

Details:

Micrographs are unaligned movies comprised of 59 frames each (accumulating 88.5 electron per squared Angstrom in a 1.5 second exposure)

Files:

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2. aligned and dose-weighted micrographs

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

6926

Image size:

(4096, 4096)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(1.065, 1.065)

Details:

Micrographs are averages of aligned and dose-weighted movies

Files:

Archives and downloads the selected files into an uncompressed zip file.

We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

It is possible to download files by specifying the file list with rsync command, etc.

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

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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)