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SHREC 2021: Classification in Cryo-electron Tomograms

Ilja Gubins, Marten L. Chaillet, Gijs Van Der Schot, M. Cristina Trueba, Remco C. Veltkamp, Friedrich Förster, Xiao Wang, Daisuke Kihara, Emmanuel Moebel, Nguyen P. Nguyen, Tommi White, Filiz Bunyak (+11 others)
2021 Eurographics Workshop on 3D Object Retrieval, EG 3DOR  
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.  ...  To promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms.  ...  Benchmark We propose a task of localization and classification of particles in the cryo-electron tomogram volume.  ... 
doi:10.2312/3dor.20211307 fatcat:4ogenb2jmzhq3pi52fjf2sknzq

VP-Detector: A 3D convolutional neural network for automated macromolecule localization and classification in cryo-electron tomograms [article]

Yu Hao, Biao Zhang, Xiaohua Wan, Rui Yan, Zhiyong Liu, Jintao Li, Shihua Zhang, Xuefeng Cui, Fa Zhang
2021 bioRxiv   pre-print
Motivation: Cryo-electron tomography (Cryo-ET) with sub-tomogram averaging (STA) is indispensable when studying macromolecule structures and functions in their native environments.  ...  VP-Detector is efficient because classification performs on the pre-calculated coordinates instead of a sliding window. Results: We evaluated the VP-Detector on simulated tomograms.  ...  Localizing and classifying the macromolecules in cryo-electron tomogram is the first step for the STA process.  ... 
doi:10.1101/2021.05.25.443703 fatcat:g42zjaooyvbm3mslcz53njnys4

Macromolecules Structural Classification with a 3D Dilated Dense Network in Cryo-electron Tomography

Shan Gao, Renmin Han, Xiangrui Zeng, Zhiyong Liu, Min Xu, Fa Zhang
2021 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
Cryo-electron tomography, combined with subtomogram averaging (STA), can reveal three-dimensional (3D) macromolecule structures in the near-native state from cells and other biological samples.  ...  In STA, to get a high-resolution 3D view of macromolecule structures, diverse macromolecules captured by the cellular tomograms need to be accurately classified.  ...  To address this issue, Cryo-Electron Tomography (cryo-ET), with the ability to reveal the structure of macromolecular complexes in a near-native state at the sub-molecular resolution, is proposed [4]  ... 
doi:10.1109/tcbb.2021.3065986 pmid:33729943 pmcid:PMC8446108 fatcat:jog5wiqeurdjxdwgzyp4swhnyi

FSCC: Few-Shot Learning for Macromolecule Classification Based on Contrastive Learning and Distribution Calibration in Cryo-Electron Tomography

Shan Gao, Shan Gao, Xiangrui Zeng, Min Xu, Fa Zhang
2022 Frontiers in Molecular Biosciences  
Cryo-electron tomography (Cryo-ET) is an emerging technology for three-dimensional (3D) visualization of macromolecular structures in the near-native state.  ...  To recover structures of macromolecules, millions of diverse macromolecules captured in tomograms should be accurately classified into structurally homogeneous subsets.  ...  Classification in Cryo-Electron Tomograms. SHREC’19 Track . Guo, Q., Lehmer, C., Martínez-Sánchez, A., Rudack, T., Beck, F., Hartmann, H., et al. (2018).  ... 
doi:10.3389/fmolb.2022.931949 pmid:35865006 pmcid:PMC9294403 doaj:dc350e948bbe4f44aecf88b3fd98aed1 fatcat:cw4udo7nc5cdtpcmwv6vp7prhy

DISCA: high-throughput cryo-ET structural pattern mining by deep unsupervised clustering [article]

Xiangrui Zeng, Anson Kahng, Liang Xue, Julia Mahamid, Yi-Wei Chang, Min Xu
2021 bioRxiv   pre-print
Cryo-electron tomography directly visualizes heterogeneous macromolecular structures in complex cellular environments, but existing computer-assisted sorting approaches are low-throughput or inherently  ...  Diverse structures emerging from sorted subsets enable systematic unbiased recognition of macromolecular complexes in situ.  ...  Acknowledgements This work was supported in part by U.S. NIH grants R01GM134020 and P41GM103712, NSF  ... 
doi:10.1101/2021.05.16.444381 fatcat:qul2vproqreexka46mttrri4tu

TomoTwin: Generalized 3D Localization of Macromolecules in Cryo-electron Tomograms with Structural Data Mining [article]

Gavin Rice, Thorsten Wagner, Markus Stabrin, Stefan Raunser
2022 bioRxiv   pre-print
To assist in this crucial particle picking step, we present TomoTwin: a robust, first in class general picking model for cryo-electron tomograms based on deep metric learning.  ...  By embedding tomograms in an information-rich, high-dimensional space which separates macromolecules according to their 3-dimensional structure, TomoTwin allows users to identify proteins in tomograms  ...  in Cryo-Electron Tomograms (SHREC) competition where contestants submit algorithms to localize proteins in tomograms with a benchmark set by template matching 18 .  ... 
doi:10.1101/2022.06.24.497279 fatcat:e55uck2u3bewxer2uxg3jgvhxa