AIMC Topic: Cryoelectron Microscopy

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Topaz-Denoise: general deep denoising models for cryoEM and cryoET.

Nature communications Oct 15, 2020
Cryo-electron microscopy (cryoEM) is becoming the preferred method for resolving protein structures. Low signal-to-noise ratio (SNR) in cryoEM images reduces the confidence and throughput of structure determination during several steps of data proces...
Machine Learning Signal-To-Noise Ratio Particle Size Cadherins Data Collection Cryoelectron Microscopy Resin Cements
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Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo-Electron Microscopy Maps.

Angewandte Chemie (International ed. in English) May 11, 2020
In recent years, three-dimensional density maps reconstructed from single particle images obtained by electron cryo-microscopy (cryo-EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the const...
Cryoelectron Microscopy DNA Protein Structure, Secondary Humans Oligonucleotides Models, Molecular Neural Networks, Computer RNA
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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-...
Software Algorithms Deep Learning Macromolecular Substances Cryoelectron Microscopy
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Flexible Fitting of Small Molecules into Electron Microscopy Maps Using Molecular Dynamics Simulations with Neural Network Potentials.

Journal of chemical information and modeling Mar 30, 2020
Despite significant advances in resolution, the potential for cryo-electron microscopy (EM) to be used in determining the structures of protein-drug complexes remains unrealized. Determination of accurate structures and coordination of bound ligands ...
Cryoelectron Microscopy Microscopy, Electron Protein Conformation Molecular Dynamics Simulation Molecular Conformation Neural Networks, Computer
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Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps.

Scientific reports Mar 9, 2020
Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on a...
Amino Acid Sequence Protein Conformation Proteins Models, Molecular Cryoelectron Microscopy Sequence Homology Neural Networks, Computer Software Algorithms Deep Learning Humans
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Need for Cross-Validation of Single Particle Cryo-EM.

Journal of chemical information and modeling Feb 26, 2020
Cross-validation is used to determine the validity of a model on unseen data by assessing if the model is overfitted to noise. It is widely used in many fields, from artificial intelligence to structural biology in X-ray crystallography and nuclear m...
Crystallography, X-Ray Cryoelectron Microscopy Artificial Intelligence Signal-To-Noise Ratio
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Automatic identification of crossovers in cryo-EM images of murine amyloid protein A fibrils with machine learning.

Journal of microscopy Dec 29, 2019
Detecting crossovers in cryo-electron microscopy images of protein fibrils is an important step towards determining the morphological composition of a sample. Currently, the crossover locations are picked by hand, which introduces errors and is a tim...
Animals Image Processing, Computer-Assisted Mice Amyloid Machine Learning Reproducibility of Results Neural Networks, Computer Protein Conformation Cryoelectron Microscopy
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Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs.

Nature methods Oct 7, 2019
Cryo-electron microscopy is a popular method for the determination of protein structures; however, identifying a sufficient number of particles for analysis can take months of manual effort. Current computational approaches find many false positives ...
Cryoelectron Microscopy Neural Networks, Computer Image Processing, Computer-Assisted
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Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.

Nature methods Jul 29, 2019
Although structures determined at near-atomic resolution are now routinely reported by cryo-electron microscopy (cryo-EM), many density maps are determined at an intermediate resolution, and extracting structure information from these maps is still a...
Deep Learning Proteins Neural Networks, Computer Software Protein Structure, Secondary Models, Molecular Cryoelectron Microscopy Humans
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AutoCryoPicker: an unsupervised learning approach for fully automated single particle picking in Cryo-EM images.

BMC bioinformatics Jun 13, 2019
BACKGROUND: An important task of macromolecular structure determination by cryo-electron microscopy (cryo-EM) is the identification of single particles in micrographs (particle picking). Due to the necessity of human involvement in the process, curre...
Unsupervised Machine Learning Image Processing, Computer-Assisted Automation Cluster Analysis Cryoelectron Microscopy Software Algorithms
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