EMPIAR-10030 - Cryo-EM micrographs of microtubules in GDP-state obtained by copolymerization with EB3 [multiple data sets in MRC format]

EMPIAR-10030

Cryo-EM micrographs of microtubules in GDP-state obtained by copolymerization with EB3 [multiple data sets in MRC format]

Publication:

Mechanistic Origin of Microtubule Dynamic Instability and Its Modulation by EB Proteins

Zhang R, Alushin GM, Brown A, Nogales E

Cell 162 (2015) 849-859

PMID: 26234155

DOI: doi:10.1016/j.cell.2015.07.012

Related EMDB entry:

EMD-6351

Deposited:

2015-07-08

Released:

2015-08-12

Last modified:

2022-09-01

Imageset size:

425.96 GB

Imageset DOI:

10.6019/EMPIAR-10030

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. Unaligned multi-frame micrographs of microtubules in GDP-state

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

383

Image size:

(3710, 3710)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(1.32, 1.32)

Details:

Particle-picking box files can be found under /data/boxfiles

Files:

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2. Aligned single-frame micrographs of microtubules in GDP-state

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

383

Image size:

(3710, 3710)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(1.32, 1.32)

Details:

Aligned micrographs using UCSF motioncorr program

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

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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)