These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

122 related articles for article (PubMed ID: 34326541)

  • 1. Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.
    Chen M; Ludtke SJ
    Nat Methods; 2021 Aug; 18(8):930-936. PubMed ID: 34326541
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM.
    Jiménez-Moreno A; Střelák D; Filipovič J; Carazo JM; Sorzano COS
    J Struct Biol; 2021 Jun; 213(2):107712. PubMed ID: 33676034
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Integrating Molecular Models Into CryoEM Heterogeneity Analysis Using Scalable High-resolution Deep Gaussian Mixture Models.
    Chen M; Toader B; Lederman R
    J Mol Biol; 2023 May; 435(9):168014. PubMed ID: 36806476
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.
    Zhong ED; Bepler T; Berger B; Davis JH
    Nat Methods; 2021 Feb; 18(2):176-185. PubMed ID: 33542510
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 3D variability analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM.
    Punjani A; Fleet DJ
    J Struct Biol; 2021 Jun; 213(2):107702. PubMed ID: 33582281
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Accounting Conformational Dynamics into Structural Modeling Reflected by Cryo-EM with Deep Learning.
    Ye Q; Zhao Y; Li X; Zhao Y; Fu X; Zhang S; Yang Z; Zhang L
    Comb Chem High Throughput Screen; 2023; 26(3):449-458. PubMed ID: 35570549
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps.
    Si D; Moritz SA; Pfab J; Hou J; Cao R; Wang L; Wu T; Cheng J
    Sci Rep; 2020 Mar; 10(1):4282. PubMed ID: 32152330
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Probing Structural Perturbation of Biomolecules by Extracting Cryo-EM Data Heterogeneity.
    DeVore K; Chiu PL
    Biomolecules; 2022 Apr; 12(5):. PubMed ID: 35625556
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Unsupervised classification of single particles by cluster tracking in multi-dimensional space.
    Fu J; Gao H; Frank J
    J Struct Biol; 2007 Jan; 157(1):226-39. PubMed ID: 16931050
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Visualizing Conformational Space of Functional Biomolecular Complexes by Deep Manifold Learning.
    Wu Z; Chen E; Zhang S; Ma Y; Mao Y
    Int J Mol Sci; 2022 Aug; 23(16):. PubMed ID: 36012133
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.
    Maddhuri Venkata Subramaniya SR; Terashi G; Kihara D
    Nat Methods; 2019 Sep; 16(9):911-917. PubMed ID: 31358979
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction.
    Punjani A; Zhang H; Fleet DJ
    Nat Methods; 2020 Dec; 17(12):1214-1221. PubMed ID: 33257830
    [TBL] [Abstract][Full Text] [Related]  

  • 13. DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.
    Wang F; Gong H; Liu G; Li M; Yan C; Xia T; Li X; Zeng J
    J Struct Biol; 2016 Sep; 195(3):325-336. PubMed ID: 27424268
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM.
    Al-Azzawi A; Ouadou A; Max H; Duan Y; Tanner JJ; Cheng J
    BMC Bioinformatics; 2020 Nov; 21(1):509. PubMed ID: 33167860
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images.
    Jonić S
    Curr Opin Struct Biol; 2017 Apr; 43():114-121. PubMed ID: 28088125
    [TBL] [Abstract][Full Text] [Related]  

  • 16. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM.
    Wagner T; Merino F; Stabrin M; Moriya T; Antoni C; Apelbaum A; Hagel P; Sitsel O; Raisch T; Prumbaum D; Quentin D; Roderer D; Tacke S; Siebolds B; Schubert E; Shaikh TR; Lill P; Gatsogiannis C; Raunser S
    Commun Biol; 2019; 2():218. PubMed ID: 31240256
    [TBL] [Abstract][Full Text] [Related]  

  • 17. AutoCryoPicker: an unsupervised learning approach for fully automated single particle picking in Cryo-EM images.
    Al-Azzawi A; Ouadou A; Tanner JJ; Cheng J
    BMC Bioinformatics; 2019 Jun; 20(1):326. PubMed ID: 31195977
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Processing of Structurally Heterogeneous Cryo-EM Data in RELION.
    Scheres SH
    Methods Enzymol; 2016; 579():125-57. PubMed ID: 27572726
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep Learning for Validating and Estimating Resolution of Cryo-Electron Microscopy Density Maps
    Avramov TK; Vyenielo D; Gomez-Blanco J; Adinarayanan S; Vargas J; Si D
    Molecules; 2019 Mar; 24(6):. PubMed ID: 30917528
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.
    Zhu Y; Ouyang Q; Mao Y
    BMC Bioinformatics; 2017 Jul; 18(1):348. PubMed ID: 28732461
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.