AIMC Topic: Electrons

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Deep learning under mass-to-charge ratio pre-retrieval to realize electron ionization mass spectrometry library retrieval.

Rapid communications in mass spectrometry : RCM Dec 30, 2022
RATIONALE: Gas chromatography-mass spectrometry (GC-MS) is an analytical technique widely used in materials science, biomedicine, and other fields. The target compound in the experiment is identified by searching for its mass spectrum in a large mass...
Algorithms Databases, Factual Deep Learning Electrons Gas Chromatography-Mass Spectrometry
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Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning.

The Journal of chemical physics Sep 14, 2022
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A MOB pairwise decomposition ...
Machine Learning Water Electrons Normal Distribution Electricity
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Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada Feb 1, 2022
Low electron dose observation is indispensable for observing various samples using a transmission electron microscope; consequently, image processing has been used to improve transmission electron microscopy (TEM) images. To apply such image processi...
Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Electrons Microscopy, Electron, Transmission
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mCNN-ETC: identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences.

Briefings in bioinformatics Jan 17, 2022
In the past decade, convolutional neural networks (CNNs) have been used as powerful tools by scientists to solve visual data tasks. However, many efforts of convolutional neural networks in solving protein function prediction and extracting useful in...
Humans Neural Networks, Computer Proteins Amino Acid Sequence Electrons Biological Evolution
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Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America Sep 28, 2021
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...
Neural Networks, Computer Artificial Intelligence Algorithms Animals Neuronal Plasticity Models, Neurological Nickel Electrons Synapses Insulator Elements Aplysia
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Automatic recognition of ligands in electron density by machine learning.

Bioinformatics (Oxford, England) Feb 1, 2019
MOTIVATION: The correct identification of ligands in crystal structures of protein complexes is the cornerstone of structure-guided drug design. However, cognitive bias can sometimes mislead investigators into modeling fictitious compounds without so...
Machine Learning Algorithms Protein Binding Electrons Ligands Binding Sites
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