Data · dataset · 2022
SHREC Cryo-ET 2019 Dataset: Classification in Cryo-Electron Tomograms
Listed in IISH Dataverse
Different imaging techniques allow us to study the organization of life at different scales.
Description
Cryo-electron tomography (cryo-ET) has the ability to three-dimensionally visualize the cellular architecture as well as the structural details of macro-molecular assemblies under near-native conditions. Due to beam sensitivity of biological samples, an inidividual tomogram has a maximal resolution of 5 nanometers.
By averaging volumes, each depicting copies of the same type of a molecule, resolutions beyond 4 Å have been achieved. Key in this process is the ability to localize and classify the components of interest, which is challenging due to the low signal-to-noise ratio. Innovation in computational methods remains key to mine biological information from the tomograms.
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To promote such innovation, we organize this SHREC track and provide a simulated dataset with the goal of establishing a benchmark in localization and classification of biological particles in cryo-electron tomograms. The publicly available dataset contains ten reconstructed tomograms obtained from a simulated cell-like volume. Each volume contains twelve different types of proteins, varying in size and structure.
Participants had access to 9 out of 10 of the cell-like ground-truth volumes for learning-based methods, and had to predict protein class and location in the test tomogram. You can find more details in the related publication and on the contest webpage.
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FXSKKQV ↗
landing page · from datasets iisg amsterdam
- DOI doi.org/10.34894/xskkqv ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 1
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FXSKK… ↗
metadata API · from datasets iisg amsterdam
Topics
- Stated by source
- Medicine, Health and Life Sciences
- From keywords
- Life Sciences · Medicine & Health
- Inferred from text
- Imaging 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/XSKKQV | 12 d ago | JSON v1 |
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| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[modality].local:modality:imaging | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (75%) |
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| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
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