EMPIAR-12706 - Single particle cryo-EM micrographs of raiA RNA [multiple data sets in MRC format]

EMPIAR-12706

Single particle cryo-EM micrographs of raiA RNA [multiple data sets in MRC format]

Publication:

Naturally ornate RNA-only complexes revealed by cryo-EM

Kretsch RC, Wu Y, Shabalina SA, Lee H, Nye G, Koonin EV, Gao A, Chiu W, Das R

bioRxiv (2024)

DOI: 10.1101/2024.12.08.627333

Related EMDB entry:

EMD-48162

Deposited:

2024-12-05

Released:

2025-06-27

Last modified:

2025-06-27

Imageset size:

855.30 GB

Imageset DOI:

10.6019/EMPIAR-12706

Experimental metadata:

Download xml json

Contains:

micrographs - single frame
picked particles - single frame - processed

Image Sets

1. Aligned and dose-weight averaged micrographs of raiA RNA.

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

8355

Image size:

(5760, 4092)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.864, 0.864)

Details:

The micrographs are the dose-weighted average by patch motion correction in cryosparc.

Files:

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rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

2. Particle images of raiA RNA.

Category:

picked particles - single frame - processed

Image format:

MRC

No. of images or tilt series:

318464

Image size:

(320, 320)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.864, 0.864)

Details:

Particle parameters are from the final C1 reconstruction of raiA.

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)

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)