Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes with a number of challenges, mainly low signal-to-noise and inability to obtain images from all angles. Computational methods are key to analyze cryo-electron tomograms.
\n\nTo promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms. Our publicly available dataset contains ten tomographic reconstructions of simulated cell-like volumes. Each volume contains twelve different types of complexes, varying in\nsize, function and structure.
\n\nIn this paper, we have evaluated seven different methods of finding and classifying proteins. Seven research groups present results obtained with learning-based methods and trained on the simulated dataset, as well as a baseline template matching (TM), a traditional method widely used in cryo-ET research. We show that learning-based approaches can achieve notably better localization and classification performance than TM. We also experimentally confirm that there is a negative relationship between particle size and performance for all methods.
\n\nYou can find more details in the related publication and on the contest webpage.
"},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2021-09-01"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Medicine, Health and Life Sciences"]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Gubins, Ilja and Chaillet, Marten L. and Schot, Gijs van der and Trueba, M. Cristina and Veltkamp, Remco C. and Förster, Friedrich and Wang, Xiao and Kihara, Daisuke and Moebel, Emmanuel and Nguyen, Nguyen P. and White, Tommi and Bunyak, Filiz and Papoulias, Giorgos and Gerolymatos, Stavros and Zacharaki, Evangelia I. and Moustakas, Konstantinos and Zeng, Xiangrui and Liu, Sinuo and Xu, Min and Wang, Yaoyu and Chen, Cheng and Cui, Xuefeng and Zhang, Fa (2021). SHREC 2021: Classification in cryo-electron tomograms. Eurographics Workshop on 3D Object Retrieval"},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"10.2312/3dor.20211307"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.2312/3dor.20211307"}}]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Gubins, Ilja"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2022-08-25"}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/XRTJMA"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"2.0"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:87b25ab3-49d7-4e77-8207-51c37a53fe8c"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-283bde80-2f32-485d-a090-0d5df6144cda"}]}},"files":[{"description":"Contest dataset without test ground truth data. This is what contest participants had access to at the beginning of the contest.","label":"shrec21_contest_dataset.zip","restricted":false,"version":1,"datasetVersionId":25127,"dataFile":{"id":309090,"persistentId":"","filename":"shrec21_contest_dataset.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":7823307210,"description":"Contest dataset without test ground truth data. This is what contest participants had access to at the beginning of the contest.","storageIdentifier":"surf://store:182d1f67226-4260027963a9","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"ee02e65571bd5795cc6fe701407bde53931022f2"},"tabularData":false,"creationDate":"2022-08-25","publicationDate":"2022-08-25","lastUpdateTime":"2023-06-26T08:12:02Z","fileAccessRequest":false}},{"description":"Additional difference dataset containing test ground truth and evaluation script. This has been released at the end of the contest for all contest participants.","label":"shrec21_diff_dataset.zip","restricted":false,"version":2,"datasetVersionId":25127,"dataFile":{"id":309091,"persistentId":"","filename":"shrec21_diff_dataset.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":73174362,"description":"Additional difference dataset containing test ground truth and evaluation script. This has been released at the end of the contest for all contest participants.","storageIdentifier":"surf://store:182d1f90b6c-b990c719f430","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"38b91f62d95e143d3292dd3ba1a2e5996bce084b"},"tabularData":false,"creationDate":"2022-08-25","publicationDate":"2022-08-25","lastUpdateTime":"2023-06-26T08:12:02Z","fileAccessRequest":false}},{"description":"Full dataset as the other one with one big difference: this dataset does not have random mirroring of the particles, allowing full exact correspondence between rotations in ground truth file and tomograms.","label":"shrec21_full_dataset_no_mirroring.zip","restricted":false,"version":2,"datasetVersionId":25127,"dataFile":{"id":374630,"persistentId":"","filename":"shrec21_full_dataset_no_mirroring.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":9016507329,"description":"Full dataset as the other one with one big difference: this dataset does not have random mirroring of the particles, allowing full exact correspondence between rotations in ground truth file and tomograms.","storageIdentifier":"surf://store:188e88409a7-377510bb76cf","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"ec08952ee3f83f8accef604ba0cc0cb7f6083b07"},"tabularData":false,"creationDate":"2023-06-23","publicationDate":"2023-06-26","lastUpdateTime":"2023-06-26T08:12:02Z","fileAccessRequest":false}},{"description":"Full dataset containing both original dataset released at the beginning of the contest and the diff dataset released at the end of the contest.","label":"shrec21_full_dataset.zip","restricted":false,"version":2,"datasetVersionId":25127,"dataFile":{"id":309088,"persistentId":"","filename":"shrec21_full_dataset.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":7897018167,"description":"Full dataset containing both original dataset released at the beginning of the contest and the diff dataset released at the end of the contest.","storageIdentifier":"surf://store:182d1fc3513-ad558851989b","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"9d24c0826720849ebbd59c8bdbceb8cbf9ee8d1a"},"tabularData":false,"creationDate":"2022-08-25","publicationDate":"2022-08-25","lastUpdateTime":"2023-06-26T08:12:02Z","fileAccessRequest":false}},{"description":"This dataset contains additional ground truth files, originally not part of the contest: full resolution and noise-free projections as well as original unbinned source \"grandmodel\" volumes used for the projections.","label":"shrec21_original_groundtruth.zip","restricted":false,"version":2,"datasetVersionId":25127,"dataFile":{"id":309089,"persistentId":"","filename":"shrec21_original_groundtruth.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":6829297135,"description":"This dataset contains additional ground truth files, originally not part of the contest: full resolution and noise-free projections as well as original unbinned source \"grandmodel\" volumes used for the projections.","storageIdentifier":"surf://store:182d201a3c3-e69d366f1f33","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"d956d4ec44113e509a43ac9b0401c079af47d423"},"tabularData":false,"creationDate":"2022-08-25","publicationDate":"2022-08-25","lastUpdateTime":"2023-06-26T08:12:02Z","fileAccessRequest":false}}]}}}