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Deposition

CZII - CryoET Object Identification Challenge

  • Deposition ID:CZCDP-10310

Release Date: 2024-10-30

Last Modified: 2024-10-30

key visualization for CZII - CryoET Object Identification Challenge

Deposition Overview

Experimental and simulated training data for the CryoET Object Identification Challenge. Each dataset contains tilt series, alignments, tomograms and ground truth annotations for six protein complexes (Apo-ferritin, Beta-amylase, Beta-galactosidase, cytosolic ribosomes, thyroglobulin and VLP). Curation procedures are described in detail in the accompanying paper. Details on how the dataset is used in the competition are available on the competition page.

Authors

Ariana Peck, Yue Yu, Jonathan Schwartz, Anchi Cheng, Utz Heinrich Ermel, Saugat Kandel, Dari Kimanius, Elizabeth Montabana, Daniel Serwas, Hannah Siems, Zhuowen Zhao, Shawn Zheng, Matthias Haury, David Agard, Clinton Potter, Bridget Carragher, Kyle I. S. Harrington, Mohammadreza Paraan

Deposition Data

Annotations:231

Related Databases

Annotation Methods Summary

Method Type

Hybrid

Method Links

Method Type

Hybrid

Method Links

Datasets with Deposition Data

2 of 2 Datasets

Dataset Name

Organism

Runs

With deposition data

Annotations

Deposition only

Annotated Objects

Deposition only

key visualization for CZII - CryoET Object Identification Challenge - Simulated Training Data

CZII - CryoET Object Identification Challenge - Simulated Training Data

Dataset ID: DS-10441

Jonathan Schwartz, Kyle I. S. Harrington, Mohammadreza Paraan

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27

189
  • Beta-amylase
  • Beta-galactosidase
  • cytosolic ribosome
  • 4 More Objects
key visualization for CZII - CryoET Object Identification Challenge - Experimental Training Data

CZII - CryoET Object Identification Challenge - Experimental Training Data

Dataset ID: DS-10440

Ariana Peck, Yue Yu, Jonathan Schwartz, ... , Kyle I. S. Harrington, Mohammadreza Paraan

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7

42
  • Beta-amylase
  • Beta-galactosidase
  • cytosolic ribosome
  • 3 More Objects