Mass Spectrometry Techniques and Applications

This paper introduces a probabilistic framework that integrates mass spectrometry and retention time data to improve small molecule identification in LC-MS experiments.

ZODIAC improves molecular formula annotation in metabolomics by combining SIRIUS results with Gibbs sampling, reducing errors and discovering novel compounds.

rMSIcleanup annotates and removes matrix-related peaks in MSI data, improving post-processing by reducing redundant signals.

The paper introduces DeepEI, a deep learning method that predicts molecular fingerprints from EI-MS spectra to improve compound identification accuracy.

The paper introduces a linear deconvolution method using optimal transport to improve accuracy in mass spectrometry by reducing sensitivity to measurement inaccuracies.

The paper analyzes UVPD fragmentation of tryptic peptides at 213 nm, finding that sequence coverage and fragment intensity correlate with precursor charge density and that aromatic amino acids enhance fragmentation.

This paper develops a high-sensitivity lipidomics workflow using TIMS and PASEF, enabling deeper lipid analysis from minimal samples with improved speed and coverage.

The paper investigates how cocaine and methylphenidate affect brain phospholipids in Drosophila using mass spectrometry imaging, showing persistent changes and partial reversal with methylphenidate.

The paper integrates mass spectrometry imaging tools into Galaxy to enable accessible, reproducible, and transparent analysis of MSI data.

This study combines ambient ionization mass spectrometry imaging with microscopy to improve tumor margin detection in mouse tissues by identifying potential biomarkers.

The paper describes a workflow for creating MS/MS reference spectra in the GNPS infrastructure, achieving 99.2% accurate annotation of chemical standards.

The paper develops a mass spectrometry imaging method to map sterol distributions in mouse brain tissue, revealing spatial cholesterol metabolism patterns in wild-type and cholesterol 24S-hydroxylase knock-out mice.

ColocAI quantifies co-localization between mass spectrometry images using AI, outperforming existing methods and providing insights into 10,273 molecules from public datasets.

The paper develops methods to improve image processing for tellurium-based imaging mass cytometry data by addressing background noise and signal-to-noise ratio issues.

The paper introduces a method using ion co-localization features to classify tumors from MSI data, addressing batch effects and generating hypotheses about sample classes.

The paper develops machine and deep learning methods to identify off-sample ions in mass spectrometry images, achieving high F1 scores.

Deuteros is a software tool for rapid analysis and visualization of differential HDX-MS data, designed to work with Waters DynamX.

The paper identifies non-covalently-associated peptides in mass spectrometry that can mislead crosslink analysis and proposes methods to distinguish them from true crosslinks.

The paper introduces the timsTOF Pro instrument with online PASEF, achieving high sensitivity and reproducibility in proteomics.

The paper investigates how cross-linker length and molecular motions affect XL-MS depth and distance restraints for protein-protein docking.