BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

271 related articles for article (PubMed ID: 35858496)

  • 1. MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms.
    Lamm L; Righetto RD; Wietrzynski W; Pöge M; Martinez-Sanchez A; Peng T; Engel BD
    Comput Methods Programs Biomed; 2022 Sep; 224():106990. PubMed ID: 35858496
    [TBL] [Abstract][Full Text] [Related]  

  • 2. VP-Detector: A 3D multi-scale dense convolutional neural network for macromolecule localization and classification in cryo-electron tomograms.
    Hao Y; Wan X; Yan R; Liu Z; Li J; Zhang S; Cui X; Zhang F
    Comput Methods Programs Biomed; 2022 Jun; 221():106871. PubMed ID: 35584579
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Simulating cryo electron tomograms of crowded cell cytoplasm for assessment of automated particle picking.
    Pei L; Xu M; Frazier Z; Alber F
    BMC Bioinformatics; 2016 Oct; 17(1):405. PubMed ID: 27716029
    [TBL] [Abstract][Full Text] [Related]  

  • 4. PickYOLO: Fast deep learning particle detector for annotation of cryo electron tomograms.
    Genthe E; Miletic S; Tekkali I; Hennell James R; Marlovits TC; Heuser P
    J Struct Biol; 2023 Sep; 215(3):107990. PubMed ID: 37364763
    [TBL] [Abstract][Full Text] [Related]  

  • 5. TomoTwin: generalized 3D localization of macromolecules in cryo-electron tomograms with structural data mining.
    Rice G; Wagner T; Stabrin M; Sitsel O; Prumbaum D; Raunser S
    Nat Methods; 2023 Jun; 20(6):871-880. PubMed ID: 37188953
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep Learning-Based Segmentation of Cryo-Electron Tomograms.
    Heebner JE; Purnell C; Hylton RK; Marsh M; Grillo MA; Swulius MT
    J Vis Exp; 2022 Nov; (189):. PubMed ID: 36440884
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms.
    Moebel E; Martinez-Sanchez A; Lamm L; Righetto RD; Wietrzynski W; Albert S; Larivière D; Fourmentin E; Pfeffer S; Ortiz J; Baumeister W; Peng T; Engel BD; Kervrann C
    Nat Methods; 2021 Nov; 18(11):1386-1394. PubMed ID: 34675434
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.
    Zeng X; Leung MR; Zeev-Ben-Mordehai T; Xu M
    J Struct Biol; 2018 May; 202(2):150-160. PubMed ID: 29289599
    [TBL] [Abstract][Full Text] [Related]  

  • 9. DRPnet: automated particle picking in cryo-electron micrographs using deep regression.
    Nguyen NP; Ersoy I; Gotberg J; Bunyak F; White TA
    BMC Bioinformatics; 2021 Feb; 22(1):55. PubMed ID: 33557750
    [TBL] [Abstract][Full Text] [Related]  

  • 10. DeepETPicker: Fast and accurate 3D particle picking for cryo-electron tomography using weakly supervised deep learning.
    Liu G; Niu T; Qiu M; Zhu Y; Sun F; Yang G
    Nat Commun; 2024 Mar; 15(1):2090. PubMed ID: 38453943
    [TBL] [Abstract][Full Text] [Related]  

  • 11. ColabSeg: An interactive tool for editing, processing, and visualizing membrane segmentations from cryo-ET data.
    Siggel M; Jensen RK; Maurer VJ; Mahamid J; Kosinski J
    J Struct Biol; 2024 Jun; 216(2):108067. PubMed ID: 38367824
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Subtomogram averaging from cryo-electron tomograms.
    Leigh KE; Navarro PP; Scaramuzza S; Chen W; Zhang Y; Castaño-Díez D; Kudryashev M
    Methods Cell Biol; 2019; 152():217-259. PubMed ID: 31326022
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens.
    Böhning J; Bharat TAM; Collins SM
    Structure; 2022 Mar; 30(3):408-417.e4. PubMed ID: 35051366
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Hierarchical detection and analysis of macromolecular complexes in cryo-electron tomograms using Pyto software.
    Lučić V; Fernández-Busnadiego R; Laugks U; Baumeister W
    J Struct Biol; 2016 Dec; 196(3):503-514. PubMed ID: 27742578
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Current data processing strategies for cryo-electron tomography and subtomogram averaging.
    Pyle E; Zanetti G
    Biochem J; 2021 May; 478(10):1827-1845. PubMed ID: 34003255
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Volumetric macromolecule identification in cryo-electron tomograms using capsule networks.
    Hajarolasvadi N; Sunkara V; Khavnekar S; Beck F; Brandt R; Baum D
    BMC Bioinformatics; 2022 Aug; 23(1):360. PubMed ID: 36042418
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Cryo-Electron Tomography and Subtomogram Averaging.
    Wan W; Briggs JA
    Methods Enzymol; 2016; 579():329-67. PubMed ID: 27572733
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography.
    Morado DR; Hu B; Liu J
    J Vis Exp; 2016 Jan; (107):e53608. PubMed ID: 26863591
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation.
    Liu S; Ban X; Zeng X; Zhao F; Gao Y; Wu W; Zhang H; Chen F; Hall T; Gao X; Xu M
    BMC Bioinformatics; 2020 Sep; 21(1):399. PubMed ID: 32907544
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.