EMPIAR-10186 - T. acidophilum 20S proteasome core movies obtained using Talos Arctica operating at 200 kV equipped with a K2 – image shift used for exposure target navigation [262 multi-frame micrographs composed of 68 frames each in MRC format]

EMPIAR-10186

T. acidophilum 20S proteasome core movies obtained using Talos Arctica operating at 200 kV equipped with a K2 – image shift used for exposure target navigation [262 multi-frame micrographs composed of 68 frames each in MRC format]

Publication:

Achieving better-than-3-Å resolution by single-particle cryo-EM at 200 keV

Herzik Jr MA, Wu M, Lander GC

Nature methods 14 (2017) 1075-1078

PMID: 28991891

DOI: 10.1038/nmeth.4461

Related EMDB entry:

EMD-8742

Deposited:

2018-05-03

Released:

2018-05-11

Last modified:

2018-05-11

Imageset size:

945.46 GB

Imageset DOI:

10.6019/EMPIAR-10186

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Raw, unaligned movie stacks of T. acidophilum 20S proteasome core acquired on a Talos Arctica using a K2 direct electron detector - image shift used for exposure navigation

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

262

Image size:

(7420, 7676)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.46, 0.46)

Details:

Raw, unaligned super-resolution frame stacks (68 frames) of T. acidophilum 20S proteasome core in vitreous ice imaged on a Talos Arctica using a K2 direct electron detector - image shift used for exposure navigation. Images used for normalizations are also included.

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Citations

AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.

Ramírez-Aportela E, Zarrabeitia OL, Fonseca YC, Ceska T, Subramaniam S, Carazo JM, Sorzano COS. (2026)

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Yu C, Xu Z, Zeng Q, Wan X, El-Messiry H, Zhang F, Han R. (2026)

Helical reconstruction of amyloids in cryoSPARC.

Schaefer JH, O'Neill RT, Donnelly JP, Powers ET, Kelly JW, Lander GC. (2026)

An unattended image-processing pipeline for on-the-fly quality assessment and 3D exploration in cryo-EM.

Marchán Torres D, Conesa P, Garcia A, Iceta M, Broche L, Gragera M, Linares R, Kwong HS, Chichón FJ, Svensson O, Arranz R, Effantin G, Kandiah E, Carazo JM, Sorzano COS. (2026)

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

Poudel B, Gyawali R, Dhakal A, Cheng J, Xu D. (2026)

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)

Unbend, correction of local beam-induced sample motion in cryo-EM images using a 3D spline model.

Kong L, Zottig X, Elferich J, Grigorieff N. (2026)

CryoVirusDB: An Annotated Dataset for AI-Based Virus Particle Identification in Cryo-EM Micrographs.

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

CryoWriter: a robotic solution for improved Cryo-EM grid preparation.

Kv C, Ekundayo B, Di Fabrizio M, Mohammed I, Radecke J, Stahlberg H, Kube M. (2026)