EMPIAR-11897 - Unveiling the ultrastructural landscape of extracellular matrix via lift-out cryo-FIBSEM and cryo-ET [multiple data sets in TIFF and MRC formats]

EMPIAR-11897

Unveiling the ultrastructural landscape of extracellular matrix via lift-out cryo-FIBSEM and cryo-ET [multiple data sets in TIFF and MRC formats]

Publication:

Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix

Zens B, Fäßler F, Hansen JM, Hauschild R, Datler J, Hodirnau VV, Zheden V, Alanko J, Sixt M, Schur FKM

The Journal of cell biology 223 (2024)

PMID: 38506714

DOI: 10.1083/jcb.202309125

Related EMDB entry:

EMD-18490 EMD-18493 EMD-18491 EMD-18494 EMD-18492

Deposited:

2024-01-25

Released:

2024-03-19

Last modified:

2024-11-19

Imageset size:

183.01 GB

Imageset DOI:

10.6019/EMPIAR-11897

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
tilt series
reconstructed volumes

Image Sets

1. Frames

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(2.137, 2.137)

Details:

42 tilt series consisting of maximally 61 tilts each; each image consists of 8 frames. GainRef and defects file are included.

Files:

Archives and downloads the selected files into an uncompressed zip file.

Depending on the number and size of files to be downloaded, this can take an enormous amount of time. Also, this feature is unstable and may not work properly, and checksums of downloaded files are not verified.

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)

2. Raw tilt series

Category:

tilt series

Image format:

MRC

No. of images or tilt series:

Image size:

(5760, 4092)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(2.137, 2.137)

Details:

42 tilt series; .mdoc files are included. Bad tilts were excluded from the tilt series (as described in the manuscript).

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)

3. Isonet corrected tomograms

Category:

reconstructed volumes

Image format:

MRC

No. of images or tilt series:

Image size:

(510, 720)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(17.1, 17.1)

Details:

Isonet-corrected tomograms, reconstructed from cleaned tilt series (as described in the manuscript).

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)

Browse All Files

Quick Links

Browse EMPIAR

Sample Preparation Widget

Volume Browser

Tomo Viewer Prototype

Claim entries to your ORCiD

Talks and Tutorials

EMPIAR Quick tour

Publications

Re-use study

Statistics

EMPIAR in the news

COVID-19 Data Portal

EMDB

BioImage Archive

PDBe

EMNavigator@PDBj

PDBj

Citations

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)

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)

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

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

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements.

Jones HN, Deshmukh A, Pande K. (2026)

CryoGS: High-Quality Cryo-EM Homogeneous Reconstruction by Gaussian Splatting

Zeng B, Liu S, Cheng S, Xu G, Fan H. (2026)

Point cloud deformation modeling for particle selection following cryo-EM 2D classification.

Wang X, Mo Z, Li F, Zhang F, Wan X. (2026)

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Kishore V, Debarnot V, Righetto RD, Engel BD, Dokmanić I. (2026)

CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.

Schäfer JH, Calza A, Hom K, Damodar P, Peng R, Bogdanović N, Lander GC, Stagg SM, Cianfrocco MA. (2025)