Deposition
CZII - CryoET Object Identification Challenge
- Deposition ID:CZCDP-10310
Release Date: 2024-10-30
Last Modified: 2024-10-30
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
Annotation Methods Summary
Datasets with Deposition Data
2 of 2 Datasets
Dataset Name | Organism | Runs With deposition data | Annotations Deposition only | Annotated Objects Deposition only | |
|---|---|---|---|---|---|
 | CZII - CryoET Object Identification Challenge - Experimental Training Data Dataset ID: DS-10440 Ariana Peck, Yue Yu, Jonathan Schwartz, ... , Kyle I. S. Harrington, Mohammadreza Paraan | -- | 7 | 42 |
|
 | CZII - CryoET Object Identification Challenge - Simulated Training Data Dataset ID: DS-10441 Jonathan Schwartz, Kyle I. S. Harrington, Mohammadreza Paraan | -- | 27 | 189 |
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