EMPIAR-13155 - Cryo-EM structure of the transmembrane anti-sigma factor DdvA [multiple data sets in TIFF format]

EMPIAR-13155

Cryo-EM structure of the transmembrane anti-sigma factor DdvA [multiple data sets in TIFF format]

Publication:

Structural basis for regulation of a CBASS-CRISPR-Cas defense island by a transmembrane anti-σ factor and its ECF σ partner

Bernal-Bernal D, Pantoja-Uceda D, López-Alonso JP, López-Rojo A, López-Ruiz JA, Galbis-Martínez M, Ochoa-Lizarralde B, Tascón I, Elías-Arnanz M, Ubarretxena-Belandia I, Padmanabhan S

Science advances 10 (2024)

PMID: 39454004

DOI: 10.1126/sciadv.adp1053

Related EMDB entry:

EMD-19404 EMD-19543

Deposited:

2025-01-03

Released:

2026-01-21

Last modified:

2026-01-21

Imageset size:

12.74 TB

Imageset DOI:

10.6019/EMPIAR-13155

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multi-frame micrographs of the transmembrane anti-sigma factor DdvA

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

8428

Image size:

(5760, 4092)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.6462, 0.6462)

Details:

---

Files:

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2. Unaligned multi-frame micrographs of the transmembrane anti-sigma factor DdvA

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

18335

Image size:

(5760, 4092)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.6462, 0.6462)

Details:

---

Files:

This entry cannot be downloaded from PDBj.

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.

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Citations

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)

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)

Ultrathin liquid cells for microsecond time-resolved cryo-EM.

Curtis WA, Wenz J, Krüger CR, Barrass SV, Drabbels M, Lorenz UJ. (2026)

GTpick: A deep neural network for Cryo-EM particle detection.

Ni S, Yang C, Liu Y, Zhang Y, Shi Y, Qian A, Kong R, Chang S. (2025)

Species-specific structural adaptation of the potyviral coat protein in virions and virus-like particles.

Koritnik N, Kežar A, Kavčič L, Žnidarič MT, Leonardi A, De S, Pollari M, Mäkinen K, Podobnik M. (2026)

High-resolution ab initio reconstruction enables cryo-EM structure determination of small particles

Kim K, Li H, Clarke OB. (2025)

CLEM-Reg: an automated point cloud-based registration algorithm for volume correlative light and electron microscopy.

Krentzel D, Elphick M, Domart MC, Peddie CJ, Laine RF, Shand C, Henriques R, Collinson LM, Jones ML. (2025)

CryoEMNet driven symmetry-aware molecular reconstruction through deep learning enhanced electron microscopy.

Arora S, Pan SH, Kumar S, Singh SK, Chauhan U, Alhalabi W, Arya V, Alsulami BS, Hsu CH, Chui KT, Gupta BB. (2025)

See all citations

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