EMPIAR-12098 - Particle stack from SARS-CoV-2 (wuhan variant) Spike protein in complex with the single chain fragment scFv41N single particle cryo-EM data [stack of 4991 particles in MRCS format]

EMPIAR-12098

Particle stack from SARS-CoV-2 (wuhan variant) Spike protein in complex with the single chain fragment scFv41N single particle cryo-EM data [stack of 4991 particles in MRCS format]

Publication:

SARS-CoV-2 (wuhan variant) Spike protein in complex with the single chain fragment scFv41N

Chaves-Sanjuan A, Berlinguer M, Bolognesi M

(---)

Related EMDB entry:

EMD-50420 EMD-50422 EMD-50421 EMD-50419

Deposited:

2024-05-26

Released:

2024-07-16

Last modified:

2024-07-16

Imageset size:

764.95 GB

Imageset DOI:

10.6019/EMPIAR-12098

Experimental metadata:

Download xml json

Contains:

picked particles - multiframe - unprocessed

Image Sets

1. Particle stack and .star files of the initial and the final set of particles of the SARS-CoV-2 (wuhan variant) Spike protein in complex with the single chain fragment scFv41N data set

Category:

picked particles - multiframe - unprocessed

Image format:

MRCS

No. of images or tilt series:

4991

Image size:

(400, 400)

Pixel type:

UNSIGNED 32 BIT INTEGER

Pixel spacing:

(0.889, 0.889)

Details:

The particle stack in the particle folder contains both particles of the initial set of picked particles and the final reconstruction.

Files:

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Citations

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)

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

Costa-Gomes B, Greer J, Juraschko N, Parkhurst J, Mirecka J, Famili M, Rangel-Smith C, Strickson O, Lowe A, Basham M, Burnley T. (2025)

Self-supervised learning for generalizable particle picking in cryo-EM micrographs.

Zamanos A, Koromilas P, Bouritsas G, Kastritis PL, Panagakis Y. (2025)

Laser flash melting cryo-EM samples to overcome preferred orientation.

Straub MS, Harder OF, Mowry NJ, Barrass SV, Hruby J, Drabbels M, Lorenz UJ. (2025)

In situ structure determination of conformationally flexible targets using nextPYP.

Liu HF, Zhou Y, Huang Q, Martin J, Bartesaghi A. (2025)

EMICSS: added-value annotations for EMDB entries.

Duraisamy AK, Fonseca N, Kleywegt GJ, Patwardhan A, Morris KL. (2025)

Global conformations of <i>Pichia pastoris</i> complex I are distinguished by the binding of a unique interdomain bridging subunit.

Lee CS, Grba DN, Wright JJ, Ivanov BS, Hirst J. (2025)

Overcoming Preferred Orientation in Cryo-EM With Ultrasonic Excitation During Vitrification

Williams HM, Curtis WA, Haubner M, Hruby J, Drabbels M, Lorenz UJ. (2025)

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