EMPIAR-13583 - Cryo-EM of the C. elegans EGFR (LET-23) extracellular region bound to LIN-3 (dataset 1) [multiple data sets in TIFF and MRC formats]

EMPIAR-13583

Cryo-EM of the C. elegans EGFR (LET-23) extracellular region bound to LIN-3 (dataset 1) [multiple data sets in TIFF and MRC formats]

Publication:

Ligand regulation and function of preformed EGFR dimers

Zuo Y, Schwartz HT, Walker K, Han L, Sternberg PW, Ferguson KM

Proceedings of the National Academy of Sciences of the United States of America 123 (2026)

PMID: 42475585

DOI: 10.1073/pnas.2602436123

Related EMDB entry:

EMD-73276

Deposited:

2026-05-12

Released:

2026-09-01

Last modified:

2026-09-01

Imageset size:

3.20 TB

Imageset DOI:

10.6019/EMPIAR-13583

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. Unaligned multi-frame micrographs of the C. elegans EGFR (LET-23) extracellular region bound to LIN-3 (dataset 1)

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

8853

Image size:

(11520, 8184)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.41, 0.41)

Details:

---

Files:

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2. Gain reference for K3 movies

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

Image size:

(11520, 8184)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.41, 0.41)

Details:

Gain reference used for normalization of raw K3 movies. Orientation: no rotation, Flip upsidedown for motion import in RELION; no rotation, no flip in CryoSPARC

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.

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Citations

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Ramírez-Aportela E, Zarrabeitia OL, Fonseca YC, Ceska T, Subramaniam S, Carazo JM, Sorzano COS. (2026)

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Yu C, Xu Z, Zeng Q, Wan X, El-Messiry H, Zhang F, Han R. (2026)

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

Poudel B, Gyawali R, Dhakal A, Cheng J, Xu D. (2026)

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

He L, Bartesaghi A. (2026)

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)

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)

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

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

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

Devarkar SC, Lomakin IB, Wang J, Grada A, Bunick CG. (2026)

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