AIMC Topic: Electrons

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Dynamic Electronic Structure Fluctuations in the De Novo Peptide ACC-Dimer Revealed by First-Principles Theory and Machine Learning.

Journal of chemical information and modeling Feb 14, 2025
Recent studies have reported long-range charge transport in peptide- and protein-based fibers and wires, rendering this class of materials as promising charge-conducting interfaces between biological systems and electronic devices. In the complex mol...
Peptides Density Functional Theory Machine Learning Protein Conformation Protein Multimerization Electrons Molecular Dynamics Simulation
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Machine learning-based prediction of bioactivity in HIV-1 protease: insights from electron density analysis.

Future medicinal chemistry Nov 12, 2024
To develop a model for predicting the biological activity of compounds targeting the HIV-1 protease and to establish factors influencing enzyme inhibition. Machine learning models were built based on a combination of Richard Bader's theory of Atoms ...
HIV-1 Ligands Electrons Hydrogen Bonding HIV Protease Inhibitors HIV Protease Humans Models, Molecular Machine Learning
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Machine-Learning-Assisted Materials Discovery from Electronic Band Structure.

Journal of chemical information and modeling Nov 3, 2024
Traditional methods of materials discovery, often relying on intuition and trial-and-error experimentation, are time-consuming and limited in their ability to explore the vast design space effectively. The emergence of machine learning (ML) as a powe...
Machine Learning Materials Science Cluster Analysis Algorithms Electrons
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Prediction of electron-solid interaction parameters using machine learning.

Medical physics Oct 12, 2024
BACKGROUND: Electron backscattering coefficient and electron-stopping power are essential concepts in many disciplines, from radiation to materials science, semiconductor manufacturing, and space exploration. They enable precise calculations, measure...
Electrons Machine Learning
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Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals.

Journal of chemical information and modeling Jul 15, 2024
We present a new general-purpose machine learning model that is able to predict a variety of crystal properties, including Fermi level energy and band gap, as well as spectral ones such as electronic densities of states. The model is based on atomic ...
Electrons Crystallization Models, Molecular Machine Learning
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A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions.

Journal of structural biology Dec 14, 2023
Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a very general context, including cellular in situ observations. The approach starts by collecting a se...
Cryoelectron Microscopy Deep Learning Electrons Algorithms Electron Microscope Tomography Image Processing, Computer-Assisted
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PickYOLO: Fast deep learning particle detector for annotation of cryo electron tomograms.

Journal of structural biology Jun 25, 2023
Particle localization (picking) in digital tomograms is a laborious and time-intensive step in cryogenic electron tomography (cryoET) analysis often requiring considerable user involvement, thus becoming a bottleneck for automated cryoET subtomogram ...
Electrons Electron Microscope Tomography Cryoelectron Microscopy Deep Learning Image Processing, Computer-Assisted Reproducibility of Results
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Application of machine learning and deep learning methods for hydrated electron rate constant prediction.

Environmental research Apr 25, 2023
Accurately determining the second-order rate constant with e (k) for organic compounds (OCs) is crucial in the e induced advanced reduction processes (ARPs). In this study, we collected 867 k values at different pHs from peer-reviewed publications an...
Neural Networks, Computer Deep Learning Algorithms Electrons Machine Learning
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Deep Learning-Based Segmentation of Cryo-Electron Tomograms.

Journal of visualized experiments : JoVE Nov 11, 2022
Cryo-electron tomography (cryo-ET) allows researchers to image cells in their native, hydrated state at the highest resolution currently possible. The technique has several limitations, however, that make analyzing the data it generates time-intensiv...
Electrons Cryoelectron Microscopy Software Image Processing, Computer-Assisted Deep Learning
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Concluding remarks: Challenges and future developments in biological electron cryo-microscopy.

Faraday discussions Nov 8, 2022
During the past 10 years, biological electron cryo-microscopy (cryoEM) has undergone a process of rapid transformation. Many things we could only dream about a decade ago have now become almost routine. Nevertheless, a number of challenges remain, to...
Artificial Intelligence Electrons Cryoelectron Microscopy
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