EMPIAR-12261 - Cryo electron tomography of Enterovirus 71-infected cells [49 tilt series in MRC format]

EMPIAR-12261

Cryo electron tomography of Enterovirus 71-infected cells [49 tilt series in MRC format]

Publication:

Endosome rupture enables enteroviruses to infect cells

Ishemgulova A, Mukhamedova L, Trebichalská Z, Rájecká V, Payne P, Šmerdová L, Moravcová J, Hrebík D, Buchta D, Škubník K, Füzik T, Vaňáčová Š, Nováček J, Plevka P

Communications Biology (---)

Related EMDB entry:

EMD-15711 EMD-15710

Deposited:

2024-09-04

Released:

2024-11-21

Last modified:

2024-11-21

Imageset size:

21.10 GB

Imageset DOI:

10.6019/EMPIAR-12261

Experimental metadata:

Download xml json

Contains:

tilt series

Image Sets

1. Cryo electron tomography of Enterovirus 71-infected cos-7 cells

Category:

tilt series

Image format:

MRC

No. of images or tilt series:

Image size:

(None, None)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(None, None)

Details:

Tilt series:
- pixel width and height: 5.532 Å
- Number of tilts: 49 (Enterovirus71_30mpi_tomo7, Enterovirus71_60mpi_tomo12, Enterovirus71_60mpi_tomo16, Enterovirus71_60mpi_tomo18), 41 (Enterovirus71_60mpi_tomo24, Enterovirus71_60mpi_tomo26, Enterovirus71_60mpi_tomo8)
- number of columns, rows: 3838, 3710
- dose-symmetric tilt scheme;
± 48°, 2° tilt increment (Enterovirus71_30mpi_tomo7, Enterovirus71_60mpi_tomo12, Enterovirus71_60mpi_tomo16, Enterovirus71_60mpi_tomo18), ± 50°, 2.5° tilt increment (Enterovirus71_60mpi_tomo24, Enterovirus71_60mpi_tomo26, Enterovirus71_60mpi_tomo8)
- rawtlt, angles file available
Tomograms:
- pixel width and height: 11.06 Å (Enterovirus71_30mpi_tomo7, Enterovirus71_60mpi_tomo12, Enterovirus71_60mpi_tomo16, Enterovirus71_60mpi_tomo18), 16.60 Å (Enterovirus71_60mpi_tomo24, Enterovirus71_60mpi_tomo26, Enterovirus71_60mpi_tomo8)

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Citations

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)

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

He L, Bartesaghi A. (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)