AIMC Topic: Tandem Mass Spectrometry
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Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.
International journal of molecular sciences
Oct 30, 2024
Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear ...
Advancing Anticancer Drug Discovery: Leveraging Metabolomics and Machine Learning for Mode of Action Prediction by Pattern Recognition.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Oct 21, 2024
A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action (MoA). Metabolomics combined with machine learning allowed to predict MoAs of novel anti-proliferative drug candidates, focusing on human prostate can...
LineageFilter: Improved Proteotyping of Complex Samples Using Metaproteomics and Machine Learning.
Journal of proteome research
Oct 19, 2024
Metaproteomics is a powerful tool to characterize how microbiota function by analyzing their proteic content by tandem mass spectrometry. Given the complexity of these samples, accurately assessing their taxonomical composition without prior informat...
Development of analytical "aroma wheels" for Oolong tea infusions (Shuixian and Rougui) and prediction of dynamic aroma release and colour changes during "Chinese tea ceremony" with machine learning.
Food chemistry
Oct 4, 2024
The flavour of tea as a worldwide popular beverage has been studied extensively. This study aimed to apply established flavour analysis techniques (GC-MS, GC-O-MS and APCI-MS/MS) in innovative ways to characterise the flavour profile of oolong tea in...
Metabolomic profiling of dengue infection: unraveling molecular signatures by LC-MS/MS and machine learning models.
Metabolomics : Official journal of the Metabolomic Society
Sep 21, 2024
BACKGROUND & OBJECTIVE: The progression of dengue fever to severe dengue (SD) is a major public health concern that impairs the capacity of the medical system to predict and treat dengue patients. Hence, the present study used a metabolomic approach ...
Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.
Analytical and bioanalytical chemistry
Aug 30, 2024
Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identificat...
Navigating the maze of mass spectra: a machine-learning guide to identifying diagnostic ions in O-glycan analysis.
Analytical and bioanalytical chemistry
Aug 24, 2024
Structural details of oligosaccharides, or glycans, often carry biological relevance, which is why they are typically elucidated using tandem mass spectrometry. Common approaches to distinguish isomers rely on diagnostic glycan fragments for annotati...
Optimization of the extraction process of total steroids from (Schwein.) Pat. by artificial neural network (ANN)-response surface methodology and identification of extract constituents.
Preparative biochemistry & biotechnology
Aug 23, 2024
(Schwein.) Pat has pharmacological effects such as tonifying the spleen, dispelling dampness, and strengthening the stomach, in which sterol is one of the main compounds of , but there has not been thought you to its extraction and detailed identifi...
Deep Learning Powers Protein Identification from Precursor MS Information.
Journal of proteome research
Aug 21, 2024
Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundan...
Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems.
Poultry science
Aug 14, 2024
The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-...
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