EMPIAR-11312 - LRRC8A-BRIL:C Heteromer in lipid nanodiscs [multiple data sets in TIFF and MRCS formats]

EMPIAR-11312

LRRC8A-BRIL:C Heteromer in lipid nanodiscs [multiple data sets in TIFF and MRCS formats]

Publication:

Structural basis for assembly and lipid-mediated gating of LRRC8A:C volume-regulated anion channels

Kern DM, Bleier J, Mukherjee S, Hill JM, Kossiakoff AA, Isacoff EY, Brohawn SG

bioRxiv (2022)

PMID: 30775971

DOI: 10.1101/2022.07.31.502239

Related EMDB entry:

EMD-27686 EMD-27687

Deposited:

2022-08-15

Released:

2023-03-14

Last modified:

2023-03-14

Imageset size:

2.42 TB

Imageset DOI:

10.6019/EMPIAR-11312

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
picked particles - multiframe - processed

Image Sets

1. Unaligned tif movies for LRRC8ABRIL:C in lipid nanodiscs

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

3906

Image size:

(11520, 8184)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.524, 0.524)

Details:

Gain reference in dm4 and mrc form is included in the folder with the movies. In RELION, the gain must be flipped upside down. To match our motion correction settings, use 0.9948 e/Å2 dose per frame and use bin 2 to produce mrc at the physical pixel size of 1.048Å/px.

Files:

選択したファイルを無圧縮zipファイルにアーカイブ化してダウンロードします。

ダウンロードするファイル数やサイズによっては、膨大な時間がかかります。また、この機能は不安定で正常に動作しない可能性があり、ダウンロードされたファイルのチェックサムは検証されません。

rsync、aspera、globus 等の利用をおすすめします。

選択したファイルのリストをダウンロードします。

rsyncコマンド等でファイルリストを指定してダウンロードすることが可能です。

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

2. Polished particles stacks for LRRC8A-BRIL/C in lipid nanodiscs

Category:

picked particles - multiframe - processed

Image format:

MRCS

No. of images or tilt series:

3581

Image size:

(416, 416)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(1.048, 1.048)

Details:

Contains polished particles (192,578) as 3581 mrcs files. The selected particles (176,166) for the final reconstruction are included in the main data folder. They are in RELION star format and can be imported into cryoSPARC as well for processing.

Files:

選択したファイルを無圧縮zipファイルにアーカイブ化してダウンロードします。

rsync、aspera、globus 等の利用をおすすめします。

選択したファイルのリストをダウンロードします。

rsyncコマンド等でファイルリストを指定してダウンロードすることが可能です。

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

Browse All Files

Quick Links

Browse EMPIAR

Sample Preparation Widget

Volume Browser

Tomo Viewer Prototype

Claim entries to your ORCiD

Talks and Tutorials

EMPIAR Quick tour

Publications

Re-use study

Statistics

EMPIAR in the news

COVID-19 Data Portal

EMDB

BioImage Archive

PDBe

EMNavigator@PDBj

PDBj

Citations

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)

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)

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

He L, Bartesaghi A. (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)

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)

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

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

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

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

CryoGS: High-Quality Cryo-EM Homogeneous Reconstruction by Gaussian Splatting

Zeng B, Liu S, Cheng S, Xu G, Fan H. (2026)

See all citations

Protein Data Bank Japan News

[2026-06-10]

333件のPDBエントリーが新たに公開されました。（2026-06-10付）