EMPIAR-12872 - Turnip Crinkle Virus: virus-like particles (TCV-P38) [multiple data sets in MRC and TIFF formats]

EMPIAR-12872

Turnip Crinkle Virus: virus-like particles (TCV-P38) [multiple data sets in MRC and TIFF formats]

Publication:

The specificity of RNA packaging in isometric RNA plant viruses is principally determined by replication

Saunders K, Shah S, Peyret H, Meshcheriakova Y, Richardson J, Eltschkner S, Lawson DM, Lomonossoff G

(---)

Related EMDB entry:

EMD-53398

Deposited:

2025-05-01

Released:

2025-07-30

Last modified:

2025-07-30

Imageset size:

2.78 TB

Imageset DOI:

10.6019/EMPIAR-12872

Experimental metadata:

Download xml json

Compressed by PDBj:

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

--- file not found ---

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. micrographs for Turnip Crinkle Virus: virus-like particles (TCV-P38)

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

5484

Image size:

(4096, 4096)

Pixel type:

SIGNED 16 BIT INTEGER

Pixel spacing:

(0.94, 0.94)

Details:

Unaligned multi-frame in MRC format. See publication for further details.

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2. gain reference file

Category:

micrographs - single frame

Image format:

TIFF

No. of images or tilt series:

Image size:

(4096, 4096)

Pixel type:

SIGNED 16 BIT INTEGER

Pixel spacing:

(None, None)

Details:

Gain reference file

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)

Unbend, correction of local beam-induced sample motion in cryo-EM images using a 3D spline model.

Kong L, Zottig X, Elferich J, Grigorieff N. (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)

Dual site targeting of the bacterial 70S ribosome by tetracyclines.

Devarkar SC, Lomakin IB, Wang J, Grada A, Bunick CG. (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)