EMPIAR-10212 - CryoEM reconstruction of native lens connexin-46/50 at 3.4 angstrom resolution [multiple data sets in MRC format]

EMPIAR-10212

CryoEM reconstruction of native lens connexin-46/50 at 3.4 angstrom resolution [multiple data sets in MRC format]

Publication:

Structure of native lens connexin 46/50 intercellular channels by cryo-EM

Myers JB, Haddad BG, O'Neill SE, Chorev DS, Yoshioka CC, Robinson CV, Zuckerman DM, Reichow SL

Nature 564 (2018) 372-377

PMID: 30542154

DOI: 10.1038/s41586-018-0786-7

Related EMDB entry:

EMD-9116

Deposited:

2018-09-25

Released:

2019-01-17

Last modified:

2019-06-07

Imageset size:

774.52 GB

Imageset DOI:

10.6019/EMPIAR-10212

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned frame stacks - MP38 dataset 01

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

1017

Image size:

(7676, 7420)

Pixel type:

SIGNED BYTE

Pixel spacing:

(0.665, 0.665)

Details:

Unaligned, unprocessed frame stacks. Dose rate 3.2 electrons per pixel per second. Collected in super-resolution mode. These images were used to produce the 3.4 angstrom map associated with EMD-9116.

Files:

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2. Unaligned frame stacks - MP38 dataset 02

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

1145

Image size:

(7676, 7420)

Pixel type:

SIGNED BYTE

Pixel spacing:

(0.665, 0.665)

Details:

Unaligned, unprocessed frame stacks. Dose rate 3.2 electrons per pixel per second. Collected in super-resolution mode. These images were combined with dataset 01 to produce the 3.5 angstrom map associated with EMD-9116.

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)