AIMC Topic: Cryoelectron Microscopy

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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 ...

A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.

Journal of structural biology
Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular tomograms are often complex, making it difficult to automatically isola...

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

PloS one
Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural hete...

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

BMC bioinformatics
BACKGROUND: Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands ...

DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation.

Nucleic acids research
Atomic structure modeling is a crucial step in determining the structures of protein complexes using cryo-electron microscopy (cryo-EM). This work introduces DEMO-EMol, an improved server that integrates deep learning-based map segmentation and chain...

AI-guided cryo-EM analysis untangles uromodulin lattices that safeguard kidneys.

Structure (London, England : 1993)
In this issue of Structure, Chang et al. combined deep-learning cryoelectron microscopy (cryo-EM) particle picking and heterogeneous refinement to obtain structures of human uromodulin filament lattices that were isolated from urine samples. This wor...

Next generation technologies for protein structure determination: challenges and breakthroughs in plant biology applications.

Journal of plant physiology
Advancements in structural biology have significantly deepened our understanding of plant proteins, which are central to critical biological functions such as photosynthesis, metabolism, signal transduction, and structural architechture. Gaining insi...

AITom: AI-guided cryo-electron tomography image analyses toolkit.

Journal of structural biology
Cryo-electron tomography (cryo-ET) is an essential tool in structural biology, uniquely capable of visualizing three-dimensional macromolecular complexes within their native cellular environments, thereby providing profound molecular-level insights. ...

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks.

Communications biology
Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when ...

Quantitative spatial analysis of chromatin biomolecular condensates using cryoelectron tomography.

Proceedings of the National Academy of Sciences of the United States of America
Phase separation is an important mechanism to generate certain biomolecular condensates and organize the cell interior. Condensate formation and function remain incompletely understood due to difficulties in visualizing the condensate interior at hig...