EMPIAR-12234 - Low-dose cryo-electron ptychography of Tobacco Mosaic Virus at 6.1 mrad [114 diffraction images in BIG DATA VIEWER HDF5 format]

EMPIAR-12234

Low-dose cryo-electron ptychography of Tobacco Mosaic Virus at 6.1 mrad [114 diffraction images in BIG DATA VIEWER HDF5 format]

Publication:

Low-dose cryo-electron ptychography of proteins at sub-nanometer resolution

Küçükoğlu B, Mohammed I, Guerrero-Ferreira RC, Kube M, Kube M, Radecke J, Ribet SM, Varnavides G, Leidl ML, Lau K, Nazarov S, Nazarov S, Myasnikov A, Sachse C, Müller-Caspary K, Ophus C, Stahlberg H

bioRxiv (2024)

DOI: 10.1101/2024.02.12.579607

Related EMDB entry:

EMD-19425 EMD-19885 EMD-19432 EMD-19430

Deposited:

2024-05-16

Released:

2024-11-12

Last modified:

2024-11-12

Imageset size:

128.44 GB

Imageset DOI:

10.6019/EMPIAR-12234

Experimental metadata:

Download xml json

Contains:

diffraction images

Image Sets

1. Diffraction patterns of Tobacco Mosaic Virus particles

Category:

diffraction images

Image format:

BIG DATA VIEWER HDF5

No. of images or tilt series:

114

Image size:

(None, None)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(None, None)

Details:

These are the 4D-STEM diffraction patterns of Tobacco Mosaic Virus particles. All of the information, such as acceleration voltage and scan pixel size, are available as metadata in the h5 file.

Files:

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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)