EMPIAR-10069 - Unsupervised single-particle deep classification via statistical manifold learning [multiple data sets in MRC format]

EMPIAR-10069

Unsupervised single-particle deep classification via statistical manifold learning [multiple data sets in MRC format]

Publication:

Unsupervised single-particle deep classification via statistical manifold learning

Wu J, Ma YB, Congdon C, Brett B, Chen S, Ouyang Q, Mao Y

arXiv (2016)

Related EMDB entry:

Deposited:

2016-07-06

Released:

2016-07-06

Last modified:

2017-01-03

Imageset size:

28.17 GB

Imageset DOI:

10.6019/EMPIAR-10069

Experimental metadata:

Download xml json

Version history:

2016-07-07

REL

Restructured the data into four dataset directories.

2016-07-20

REL

Added pixel sizes information.

2017-01-03

REL

The data has been re-uploaded due to reports of damaged/corrupted files. Added the citation information.

Contains:

picked particles - multiframe - processed

Image Sets

1. Unaligned particle stacks from sub-frame drift-corrected micrographs. Set 1

Category:

picked particles - multiframe - processed

Image format:

MRC

No. of images or tilt series:

16306

Image size:

(250, 250)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.86, 0.86)

Details:

Dataset1: 250 x 250 box size, 16306-particle dataset of inflammasome. These datasets were used for benchmarking the relevant algorithms for image classification.

Files:

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2. Unaligned particle stacks from sub-frame drift-corrected micrographs. Set 2

Category:

picked particles - multiframe - processed

Image format:

MRC

No. of images or tilt series:

35407

Image size:

(160, 160)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.98, 0.98)

Details:

Dataset2: 160 x 160 box size, 35407-particle dataset of free RP complex. These datasets were used for benchmarking the relevant algorithms for image classification.

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. Unaligned particle stacks from sub-frame drift-corrected micrographs. Set 3

Category:

picked particles - multiframe - processed

Image format:

MRC

No. of images or tilt series:

96488

Image size:

(180, 180)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.86, 0.86)

Details:

Dataset3: 180 x 180 box size, 96488-particle dataset of RP-CP complex. These datasets were used for benchmarking the relevant algorithms for image classification.

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)

4. Unaligned particle stacks from sub-frame drift-corrected micrographs. Set 4

Category:

picked particles - multiframe - processed

Image format:

MRC

No. of images or tilt series:

57001

Image size:

(160, 160)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.98, 0.98)

Details:

Dataset4 denotes the 160 x 160 box size, 57001-particle dataset of free RP complex. These datasets were used for benchmarking the relevant algorithms for image classification.

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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