EMPIAR-11294 - Cryo-EM study on a single, highly heterogeneous cellular fraction with megadalton complexes derived from Chaetomium thermophilum [522 multi-frame micrographs composed of 30 frames each in MRC format]

EMPIAR-11294

Cryo-EM study on a single, highly heterogeneous cellular fraction with megadalton complexes derived from Chaetomium thermophilum [522 multi-frame micrographs composed of 30 frames each in MRC format]

Publication:

Cryo-EM of a heterogeneous cellular fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote.

Semchonok DA, Kyrilis FL, Hamdi F, Kastritis PL

Journal of Structural Biology: X (---)

DOI: 10.2139/ssrn.4211492

Related EMDB entry:

EMD-15397 EMD-17629

Deposited:

2022-10-27

Released:

2023-08-18

Last modified:

2023-08-18

Imageset size:

489.38 GB

Imageset DOI:

10.6019/EMPIAR-11294

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multi-frame micrographs of heterogeneous cellular fraction (25) containing multiple endogenous protein complexes from a thermophilic eukaryote fungal Chaetomium thermophilum

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

522

Image size:

(4096, 4096)

Pixel type:

SIGNED 16 BIT INTEGER

Pixel spacing:

(0.96, 0.96)

Details:

Cryo-EM of a heterogeneous cellular fraction (25) elucidates multiple endogenous protein complexes from a thermophilic eukaryote.

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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)