AIMC Topic: Macromolecular Substances

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

Nature methods Oct 21, 2021
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...
Photosystem II Protein Complex Ribulose-Bisphosphate Carboxylase Chlamydomonas reinhardtii Electron Microscope Tomography Deep Learning Image Processing, Computer-Assisted Cryoelectron Microscopy Ribosomes Macromolecular Substances Neural Networks, Computer Algorithms
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Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Advanced materials (Deerfield Beach, Fla.) Sep 17, 2021
Oral administration is the most convenient and commonly used approach for drug delivery, while it is still a challenge to overcome the complicated gastrointestinal barriers and realize efficient macromolecular drug absorption. Here, novel magneto-res...
Blood Glucose Insulin Animals Swine Macromolecular Substances Needles Magnetic Fields Robotics Administration, Oral Drug Delivery Systems Intestine, Small Microinjections
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Robotic sample changers for macromolecular X-ray crystallography and biological small-angle X-ray scattering at the National Synchrotron Light Source II.

Journal of synchrotron radiation Aug 23, 2021
Here we present two robotic sample changers integrated into the experimental stations for the macromolecular crystallography (MX) beamlines AMX and FMX, and the biological small-angle scattering (bioSAXS) beamline LiX. They enable fully automated una...
Crystallography, X-Ray X-Rays Synchrotrons Scattering, Small Angle Equipment Design Macromolecular Substances Software Robotics
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Deep Learning of Binary Solution Phase Behavior of Polystyrene.

ACS macro letters May 31, 2021
Predicting binary solution phase behavior of polymers has remained a challenge since the early theory of Flory-Huggins, hindering the processing, synthesis, and design of polymeric materials. Herein, we take a complementary data-driven approach by bu...
Polystyrenes Polymers Temperature Macromolecular Substances Deep Learning
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CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.

Nature methods Feb 4, 2021
Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major ch...
Neural Networks, Computer Molecular Structure Macromolecular Substances Cryoelectron Microscopy
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MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning.

Journal of structural biology Apr 7, 2020
Cryo-EM Single Particle Analysis workflows require tens of thousands of high-quality particle projections to unveil the three-dimensional structure of macromolecules. Conventional methods for automatic particle picking tend to suffer from high false-...
Cryoelectron Microscopy Algorithms Software Deep Learning Macromolecular Substances
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A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.

Journal of structural biology Dec 28, 2017
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...
Cryoelectron Microscopy Software Image Processing, Computer-Assisted Macromolecular Substances Algorithms
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A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

BMC bioinformatics Jul 21, 2017
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 ...
Neural Networks, Computer Algorithms Signal-To-Noise Ratio Cryoelectron Microscopy Macromolecular Substances Hemocyanins
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Using support vector machines to improve elemental ion identification in macromolecular crystal structures.

Acta crystallographica. Section D, Biological crystallography Apr 25, 2015
In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific know...
Crystallography, X-Ray Zinc Protein Conformation Metals Macromolecular Substances Algorithms Manganese Support Vector Machine Models, Molecular Iron Nickel Calcium
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Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks.

Communications biology May 25, 2025
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 ...
Neural Networks, Computer Deep Learning Models, Molecular Cryoelectron Microscopy Normal Distribution Macromolecular Substances
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