AIMC Topic: Electron Microscope Tomography

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Isotropic reconstruction for electron tomography with deep learning.

Nature communications
Cryogenic electron tomography (cryoET) allows visualization of cellular structures in situ. However, anisotropic resolution arising from the intrinsic "missing-wedge" problem has presented major challenges in visualization and interpretation of tomog...

New opportunities in integrative structural modeling.

Current opinion in structural biology
Integrative structural modeling enables structure determination of macromolecules and their complexes by integrating data from multiple sources. It has been successfully used to characterize macromolecular structures when a single structural biology ...

CardioVinci: building blocks for virtual cardiac cells using deep learning.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Advances in electron microscopy (EM) such as electron tomography and focused ion-beam scanning electron microscopy provide unprecedented, three-dimensional views of cardiac ultrastructures within sample volumes ranging from hundreds of nanometres to ...

Volumetric macromolecule identification in cryo-electron tomograms using capsule networks.

BMC bioinformatics
BACKGROUND: Despite recent advances in cellular cryo-electron tomography (CET), developing automated tools for macromolecule identification in submolecular resolution remains challenging due to the lack of annotated data and high structural complexit...

MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells....

Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning.

ACS nano
High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) can be acquired together with energy dispersive X-ray (EDX) spectroscopy to give complementary information on the nanoparticles being imaged. Recent deep learning ...

Macromolecules Structural Classification With a 3D Dilated Dense Network in Cryo-Electron Tomography.

IEEE/ACM transactions on computational biology and 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 macromolecul...

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Nature cell biology
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...

Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms.

Nature methods
Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and rec...

Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN.

BMC bioinformatics
BACKGROUND: Cryo-electron tomography (cryo-ET) enables the 3D visualization of cellular organization in near-native state which plays important roles in the field of structural cell biology. However, due to the low signal-to-noise ratio (SNR), large ...