EMPIAR-10257 - Structure of NDH the complex I-like molecule of photosynthesis [multiple data sets in TIFF format]

EMPIAR-10257

Structure of NDH the complex I-like molecule of photosynthesis [multiple data sets in TIFF format]

Publication:

Structure of the complex I-like molecule NDH of oxygenic photosynthesis

Laughlin TG, Bayne AN, Trempe JF, Savage DF, Davies KM

Nature 566 (2019) 411-414

PMID: 30742075

DOI: 10.1038/s41586-019-0921-0

Related EMDB entry:

EMD-0415 EMD-0419 EMD-0420 EMD-0425 EMD-0418 EMD-0417

Deposited:

2019-02-23

Released:

2019-05-01

Last modified:

2019-05-01

Imageset size:

1.94 TB

Imageset DOI:

10.6019/EMPIAR-10257

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multiframe micrographs for NDH dataset1

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

2256

Image size:

(7420, 7676)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.534, 0.534)

Details:

LZW-TIFF super-resolution movies consisting of 35 frames with cumulative exposure of 50 electrons per square Angstrom. Particle metadata and stacks for "consensus", "final" and "X-cofactor" maps.

Files:

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2. Unaligned multiframe micrographs for NDH dataset2

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

1385

Image size:

(7420, 7676)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.4515, 0.4515)

Details:

LZW-TIFF super-resolution movies consisting of 30 frames with cumulative exposure of 60 electrons per square Angstrom. Particle metadata and stacks for "consensus" and "final" maps.

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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PERC: a suite of software tools for the curation of cryoEM data with application to simulation, modeling and machine learning.

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