EMPIAR-10172 - CryoET of hemagglutinin single particle with spot-to-plunge time of 100ms [multiple data sets in MRC format]

EMPIAR-10172

CryoET of hemagglutinin single particle with spot-to-plunge time of 100ms [multiple data sets in MRC format]

Publication:

Reducing effects of particle adsorption to the air-water interface in cryoEM

Noble AJ, Wei H, Dandey VP, Zhang Z, Potter CS, Carragher B

BioRxiv (---)

DOI: 10.1101/288340

Related EMDB entry:

EMD-7628

Deposited:

2018-04-03

Released:

2018-04-05

Last modified:

2018-04-05

Imageset size:

21.93 GB

Imageset DOI:

10.6019/EMPIAR-10172

Experimental metadata:

Download xml json

Contains:

tilt series

Image Sets

1. Tilt-series image stacks

Category:

tilt series

Image format:

MRC

No. of images or tilt series:

Image size:

(3712, 4984)

Pixel type:

SIGNED 16 BIT INTEGER

Pixel spacing:

(2.34, 2.34)

Details:

Not frame-aligned.
.mdoc files included.

Files:

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

2. Appion-Protomo tilt-series alignments

Category:

tilt series

Image format:

MRC

No. of images or tilt series:

Image size:

(3712, 4984)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(2.34, 2.34)

Details:

Includes a full tilt-series alignment run for each tilt-series. To view properly, navigate to the protomo_alignments folder in Appion-Protomo.

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)