AIMC Topic: Nuclear Magnetic Resonance, Biomolecular

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Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.

Nature communications Jun 7, 2019
Chemical shifts (CS) are determined from NMR experiments and represent the resonance frequency of the spin of atoms in a magnetic field. They contain a mixture of information, encompassing the in-solution conformations a protein adopts, as well as th...
Proteins Models, Molecular Magnetic Resonance Imaging Neural Networks, Computer Magnetic Resonance Spectroscopy Protein Structure, Secondary Biophysical Phenomena Amino Acids Nuclear Magnetic Resonance, Biomolecular
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NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments.

Journal of biomolecular NMR Dec 22, 2018
The growth of the biological nuclear magnetic resonance (NMR) field and the development of new experimental technology have mandated the revision and enlargement of the NMR-STAR ontology used to represent experiments, spectral and derived data, and s...
Vocabulary, Controlled Nuclear Magnetic Resonance, Biomolecular Biological Ontologies Information Storage and Retrieval Software
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Environmental metabolomics with data science for investigating ecosystem homeostasis.

Progress in nuclear magnetic resonance spectroscopy Nov 21, 2017
A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems,...
Multivariate Analysis Animals Homeostasis Nuclear Magnetic Resonance, Biomolecular Biota Ecology Metabolomics Machine Learning Ecosystem Humans Databases, Factual
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Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins.

Journal of biomedical semantics May 5, 2016
BACKGROUND: The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII fo...
Biological Ontologies Semantics Nuclear Magnetic Resonance, Biomolecular Databases, Protein Internet Proteins
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EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Protein science : a publication of the Protein Society Aug 1, 2024
Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure. The chemical shift of the resonance frequency reflects the effect of the protons in a molecule prod...
Machine Learning Deep Learning Proteins Software Protein Conformation Nuclear Magnetic Resonance, Biomolecular Amino Acid Sequence Models, Molecular
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NMRNet: a deep learning approach to automated peak picking of protein NMR spectra.

Bioinformatics (Oxford, England) Aug 1, 2018
MOTIVATION: Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would ac...
Nuclear Magnetic Resonance, Biomolecular Proteins Macromolecular Substances Deep Learning Software
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Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trai...
Protein Conformation Carbon Isotopes Nuclear Magnetic Resonance, Biomolecular Neural Networks, Computer Proteins Models, Molecular Software Proteomics
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