AIMC Topic: Mass Spectrometry
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Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.
Food chemistry
Feb 22, 2024
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...
DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.
Analytical chemistry
Feb 20, 2024
Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional v...
Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry.
Nature methods
Feb 16, 2024
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with si...
Personalized Drug Therapy: Innovative Concept Guided With Proteoformics.
Molecular & cellular proteomics : MCP
Feb 13, 2024
Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy...
Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.
Talanta
Feb 7, 2024
Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depe...
Deep Learning Enables Automatic Correction of Experimental HDX-MS Data with Applications in Protein Modeling.
Journal of the American Society for Mass Spectrometry
Jan 23, 2024
Observed mass shifts associated with deuterium incorporation in hydrogen-deuterium exchange mass spectrometry (HDX-MS) frequently deviate from the initial signals due to back and forward exchange. In typical HDX-MS experiments, the impact of these di...
Mass spectrometry-based proteomics data from thousands of HeLa control samples.
Scientific data
Jan 23, 2024
Here we provide a curated, large scale, label free mass spectrometry-based proteomics data set derived from HeLa cell lines for general purpose machine learning and analysis. Data access and filtering is a tedious task, which takes up considerable am...
Deep learning based CETSA feature prediction cross multiple cell lines with latent space representation.
Scientific reports
Jan 22, 2024
Mass spectrometry-coupled cellular thermal shift assay (MS-CETSA), a biophysical principle-based technique that measures the thermal stability of proteins at the proteome level inside the cell, has contributed significantly to the understanding of dr...
Human robotic surgery with intraoperative tissue identification using rapid evaporation ionisation mass spectrometry.
Scientific reports
Jan 10, 2024
Instantaneous, continuous, and reliable information on the molecular biology of surgical target tissue could significantly contribute to the precision, safety, and speed of the intervention. In this work, we introduced a methodology for chemical tiss...
Enabling Lipidomic Biomarker Studies for Protected Populations by Combining Noninvasive Fingerprint Sampling with MS Analysis and Machine Learning.
Journal of proteome research
Jan 3, 2024
Triacylglycerols and wax esters are two lipid classes that have been linked to diseases, including autism, Alzheimer's disease, dementia, cardiovascular disease, dry eye disease, and diabetes, and thus are molecules worthy of biomarker exploration st...
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