AIMC Topic: Mass Spectrometry

Clear Filters Showing 271 to 280 of 339 articles

Artificial neural network modelling of pharmaceutical residue retention times in wastewater extracts using gradient liquid chromatography-high resolution mass spectrometry data.

Journal of chromatography. A
The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastewater extracts is presented using artificial neural networks for the first time. Radial basis functio...

An automated high-throughput SPE micro-elution method for perfluoroalkyl substances in human serum.

Analytical and bioanalytical chemistry
An automated high-throughput solid phase extraction (SPE) micro-elution method for 8 perfluorosulfonic acids, 11 perfluorocarboxylic acids and fluorooctane sulfonamide in human serum was developed. Importance was attached to the application of small ...

Prediction of Anti-inflammatory Plants and Discovery of Their Biomarkers by Machine Learning Algorithms and Metabolomic Studies.

Planta medica
Nonsteroidal anti-inflammatory drugs are the most used anti-inflammatory medicines in the world. Side effects still occur, however, and some inflammatory pathologies lack efficient treatment. Cyclooxygenase and lipoxygenase pathways are of utmost imp...

Robotics-assisted mass spectrometry assay platform enabled by open-source electronics.

Biosensors & bioelectronics
Mass spectrometry (MS) is an important analytical technique with numerous applications in clinical analysis, biochemistry, environmental analysis, geology and physics. Its success builds on the ability of MS to determine molecular weights of analytes...

Unveiling the dark matter of the metabolome: A narrative review of bioinformatics tools for LC-HRMS-based compound annotation.

Talanta
Compound annotation, including the unveiling of dark matter in the metabolomics study represents a pivotal undertaking within the metabolomics field, serving as the linchpin for unraveling the identities and attributes of chemical entities. This narr...

AIRPred: A Deep Learning Model Predictor for Peptide Intensity Ratios in Cross-Linking Mass Spectrometry Improves Cross-Link Spectrum Matching.

Analytical chemistry
Cross-linking mass spectrometry (XL-MS) is a powerful tool in structural proteomics, offering insights into protein conformations, interactions and dynamics by linking spatially proximal residues. However, current cross-linked spectrum match (CSM) sc...

Machine learning-assisted classification and adulteration detection of fatty oils using fatty acid profiles obtained via supercritical fluid chromatography.

Journal of pharmaceutical and biomedical analysis
Fatty oils are essential in the pharmaceutical field for enhancing the solubility and oral bioavailability of drugs, as well as reducing the risk of cardiovascular diseases. Consequently, detecting adulteration in specific fatty oils is critical to e...

Real-Time Eco-AI, Electrophoresis-Correlative Data-Dependent Acquisition with AI-Based Data Processing Broadens Access to Single-Cell Mass Spectrometry Proteomics.

Angewandte Chemie (International ed. in English)
Single-cell mass spectrometry (MS) offers unprecedented sensitivity for profiling cellular proteomes, yet widespread adoption is hindered by the cost of advanced instrumentation. Here, we broaden access to single-cell proteomics by combining capillar...

DeepMS: super-fast peptide identification using end-to-end deep learning method.

Journal of molecular biology
Mass spectrometry (MS) has emerged as a powerful omics analysis technique, particularly in proteomics, where the initial step involves identifying MS spectra as peptide sequences. However, this process often requires substantial computational resourc...

ResNeXt-Based Rescoring Model for Proteoform Characterization in Top-Down Mass Spectra.

Interdisciplinary sciences, computational life sciences
In top-down proteomics, the accurate identification and characterization of proteoform through mass spectrometry represents a critical objective. As a result, achieving accuracy in identification results is essential. Multiple primary structure alter...