EMPIAR-12868 - NifLA complex from Azotobacter vinelandii [multiple data sets in TIFF and MRC formats]

EMPIAR-12868

NifLA complex from Azotobacter vinelandii [multiple data sets in TIFF and MRC formats]

Publication:

Structural analysis of the NifL-NifA complex reveals the molecular basis of anti-activation of nitrogen fixation gene expression in Azotobacter vinelandii

Bueno Batista M, Richardson J, Webster MW, Ghilarov D, Peters JW, Lawson DM, Dixon R

(---)

Related EMDB entry:

EMD-53294

Deposited:

2025-03-31

Released:

2025-07-25

Last modified:

2025-07-25

Imageset size:

2.88 TB

Imageset DOI:

10.6019/EMPIAR-12868

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. micrographs for Azotobacter vinelandii NiFLA complex

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

14218

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.831, 0.831)

Details:

unaligned multi-frame micrographs in TIFF format. See publication for further details.

Files:

This entry cannot be downloaded from PDBj.

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. gain reference file

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

Image size:

(5760, 4092)

Pixel type:

UNSIGNED 32 BIT INTEGER

Pixel spacing:

(0.831, 0.831)

Details:

Gain reference file

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.

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

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)

prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.

He L, Bartesaghi A. (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)

Dual site targeting of the bacterial 70S ribosome by tetracyclines.

Devarkar SC, Lomakin IB, Wang J, Grada A, Bunick CG. (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)

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)

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

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

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)

See all citations

Protein Data Bank Japan News