EMPIAR-11556 - Single particle reconstruction of the human LINE-1 ORF2p without substrate (apo) [multiple data sets in MRC and TIFF formats]

EMPIAR-11556

Single particle reconstruction of the human LINE-1 ORF2p without substrate (apo) [multiple data sets in MRC and TIFF formats]

Publication:

Structures, functions and adaptations of the human LINE-1 ORF2 protein

Baldwin ET, van Eeuwen T, Hoyos D, Zalevsky A, Tchesnokov EP, Sánchez R, Miller BD, Di Stefano LH, Ruiz FX, Hancock M, Işik E, Mendez-Dorantes C, Walpole T, Nichols C, Wan P, Riento K, Halls-Kass R, Augustin M, Lammens A, Jestel A, Upla P, Xibinaku K, Congreve S, Hennink M, Rogala KB, Schneider AM, Fairman JE, Christensen SM, Desrosiers B, Bisacchi GS, Saunders OL, Hafeez N, Miao W, Kapeller R, Zaller DM, Sali A, Weichenrieder O, Burns KH, Götte M, Rout MP, Arnold E, Greenbaum BD, Romero DL, LaCava J, Taylor MS

Nature 626 (2023) 194-206

PMID: 38096902

DOI: 10.1038/s41586-023-06947-z

Related EMDB entry:

EMD-40856

Deposited:

2023-05-23

Released:

2024-07-19

Last modified:

2024-07-19

Imageset size:

2.13 TB

Imageset DOI:

10.6019/EMPIAR-11556

Experimental metadata:

Download xml json

Contains:

micrographs - single frame
micrographs - multiframe

Image Sets

1. Aligned single frame micrographs of apo LINE-1 ORF2p

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

6477

Image size:

(5760, 4092)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(0.65, 0.65)

Details:

No associated particles

Files:

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2. Unaligned multiframe movies of apo LINE-1 ORF2p

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

6477

Image size:

(11520, 8184)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.325, 0.325)

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.

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Citations

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

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

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