EMPIAR-11969 - Cryo-electron tomography of mitotic chromosomes isolated from chicken DT-40 cells with annotated nucleosome positions [multiple data sets in TIFF, MRCS and MRC formats]

EMPIAR-11969

Cryo-electron tomography of mitotic chromosomes isolated from chicken DT-40 cells with annotated nucleosome positions [multiple data sets in TIFF, MRCS and MRC formats]

Publication:

Template Learning: Deep learning with domain randomization for particle picking in cryo-electron tomography

Harastani M, Patra G, Kervrann C, Eltsov M

Nature communications 16 (2025)

PMID: 41044063

DOI: 10.1038/s41467-025-63895-0

Related EMDB entry:

EMD-19823 EMD-19825

Deposited:

2024-03-14

Released:

2025-10-15

Last modified:

2025-10-15

Imageset size:

6.41 GB

Imageset DOI:

10.6019/EMPIAR-11969

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
tilt series
reconstructed volumes

Image Sets

1. Unaligned multiframe tilt images of mitotic chromosomes

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(2.075, 2.075)

Details:

Raw unaligned multi-frame micrographs were aligned, sorted and combined into tilt series stacks using Motioncor2. The tilt series were reconstructed using etomo (IMOD).
Original metadata files (.mdoc) are provided in the mdoc folder and tomograms reconstructed using etomo (IMOD) (.mrc file in Tomogram folder). The alignment information (.xf file) is in the Alignment_info folder.

Files:

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2. Aligned tilt series of mitotic chromosome

Category:

tilt series

Image format:

MRCS

No. of images or tilt series:

Image size:

(4092, 5760)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(2.075, 2.075)

Details:

Tilt series stack (.mrcs file) aligned with etomo (IMOD).

Files:

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

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Download a list of selected files.

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3. Reconstructed tomogram of mitotic chromosome

Category:

reconstructed volumes

Image format:

MRC

No. of images or tilt series:

Image size:

(1023, 1440)

Pixel type:

16 BIT FLOAT

Pixel spacing:

(8.3, 8.3)

Details:

Tomogram (4-times binned reconstructions, original pixel size 2.075 Å) from aligned tilt series (.mrcs file in TiltSeries folder). The coordinates of nucleosomes annotated by Template Learning and template matching are in the picks folder.

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

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)