EMPIAR-12536 - Dataset of apoferritin on HexAuFoil grids [multiple data sets in TIFF format]

EMPIAR-12536

Dataset of apoferritin on HexAuFoil grids [multiple data sets in TIFF format]

Publication:

Dataset of apoferritin on HexAuFoil grids

Weckener M

(---)

Related EMDB entry:

Deposited:

2025-01-24

Released:

2025-03-19

Last modified:

2025-03-19

Imageset size:

53.40 GB

Imageset DOI:

10.6019/EMPIAR-12536

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. Unaligned multi-frame micrographs of apoferritin on HexAuFoil grids

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

399

Image size:

(4096, 4096)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.729, 0.729)

Details:

Raw movie files with 50 frames.

Files:

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

Depending on the number and size of files to be downloaded, this can take an enormous amount of time. Also, this feature is unstable and may not work properly, and checksums of downloaded files are not verified.

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)

2. Gain reference file for unaligned multi-frame micrographs of apoferritin on HexAuFoil grids

Category:

micrographs - single frame

Image format:

TIFF

No. of images or tilt series:

Image size:

(4096, 4096)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(None, None)

Details:

Gain reference file for raw movies of apoferritin on HexAuFoil grids.

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)