AIMC Topic: Mass Spectrometry

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De novo design of high-affinity binders of bioactive helical peptides.

Nature Dec 18, 2023
Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity ...
Luminescent Measurements Diffusion Proteins Models, Molecular Protein Structure, Secondary Glucagon Parathyroid Hormone Substrate Specificity Computer-Aided Design Deep Learning Biosensing Techniques Mass Spectrometry Peptides
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Deep graph convolutional network for small-molecule retention time prediction.

Journal of chromatography. A Oct 13, 2023
The retention time (RT) is a crucial source of data for liquid chromatography-mass spectrometry (LCMS). A model that can accurately predict the RT for each molecule would empower filtering candidates with similar spectra but differing RT in LCMS-base...
Mass Spectrometry Chromatography, Liquid Algorithms Neural Networks, Computer Machine Learning
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Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Oct 12, 2023
Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous algorithms, many of which were derived with the aid of artificial intelligence, were brought up in a...
Mass Spectrometry Metabolomics Humans Artificial Intelligence Meningitis Metabolome
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Bioactivation and reactivity research advances - 2022 year in review‡.

Drug metabolism reviews Aug 22, 2023
With the 50th year mark since the launch of journal, the field of drug metabolism and bioactivation has advanced exponentially in the past decades (Guengerich 2023).This has, in a major part, been due to the continued advances across the whole spect...
Artificial Intelligence Machine Learning Mass Spectrometry Humans
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Mapping HDX-MS Data to Protein Conformations through Training Ensemble-Based Models.

Journal of the American Society for Mass Spectrometry Aug 7, 2023
An original approach that adopts machine learning inference to predict protein structural information using hydrogen-deuterium exchange mass spectrometry (HDX-MS) is described. The method exploits an in-house optimization program that increases the r...
Hydrogen Deuterium Exchange-Mass Spectrometry Deuterium Exchange Measurement Proteins Protein Conformation Mass Spectrometry Artificial Intelligence
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Machine learning-guided REIMS pattern recognition of non-dairy cream, milk fat cream and whipping cream for fraudulence identification.

Food chemistry Jul 24, 2023
The illegal adulteration of non-dairy cream in milk fat cream during the manufacturing process of baked goods has significantly hindered the robust growth of the dairy industry. In this study, a method based on rapid evaporative ionization mass spect...
Machine Learning Algorithms Animals Mass Spectrometry Milk Discriminant Analysis
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Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning.

Journal of chromatography. A Jun 19, 2023
Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering effi...
Metabolomics Chromatography, Liquid Mass Spectrometry Software Deep Learning
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DeepSP: A Deep Learning Framework for Spatial Proteomics.

Journal of proteome research Jun 14, 2023
The study of protein subcellular localization (PSL) is a fundamental step toward understanding the mechanism of protein function. The recent development of mass spectrometry (MS)-based spatial proteomics to quantify the distribution of proteins acros...
Proteins Proteomics Mass Spectrometry Algorithms Deep Learning
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Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data.

Environmental science & technology Jun 6, 2023
Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest po...
Machine Learning Mass Spectrometry
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A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data.

Proteomics May 3, 2023
Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. ...
Models, Molecular Cross-Linking Reagents Mass Spectrometry Proteins Deep Learning
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