EMPIAR-11024 - E. coli 50S ribosome bound to compounds VM2 and VS1 [multiple data sets in TIFF and MRC formats]

EMPIAR-11024

E. coli 50S ribosome bound to compounds VM2 and VS1 [multiple data sets in TIFF and MRC formats]

Publication:

50S E. coli ribosome bound to VM2 and VS1

Pellegrino J

(---)

Related EMDB entry:

EMD-26657

Deposited:

2022-04-07

Released:

2022-06-17

Last modified:

2022-06-17

Imageset size:

1.30 TB

Imageset DOI:

10.6019/EMPIAR-11024

Experimental metadata:

Download xml json

Contains:

micrographs - single frame
micrographs - multiframe

Image Sets

1. Unaligned movies of 50S ribosome bound to VM2 and VS1

Category:

micrographs - single frame

Image format:

TIFF

No. of images or tilt series:

2043

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.665, 0.665)

Details:

---

Files:

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2. Aligned, motioncorrected micrographs of 50S ribosome bound to VM2 and VS1

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.665, 0.665)

Details:

---

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

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)

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)

See all citations

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