Tandem Mass Spectral Databases and Their Use in Non-Targeted Metabolomics.

Comprehensive LC-MS Metabolomics Data Processing with notame R/Bioconductor Package.

Liquid chromatography-mass spectrometry (LC-MS) is widely used in metabolomics. Raw LC-MS data is relatively complex, consisting of molecular features originating not only from unique metabolites but also from redundant adducts, in-source fragments, artifacts, and impurities. It is also prone to signal intensity drift...

Computational Tools for LC-IMS-MS Data Processing in Metabolomics.

A Practical Guide to Dereplication in Natural Products Metabolomics.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics has become a central approach for characterizing the chemical diversity of biological systems, particularly in natural product discovery. However, the scale and complexity of untargeted LC-MS/MS datasets present a persistent challenge: only a...

LC-MS Data Processing Using xcms.

Liquid chromatography-mass spectrometry (LC-MS) is a key technology in metabolomics, enabling high-throughput detection of small molecules across diverse biological samples. However, raw LC-MS data are complex, requiring careful preprocessing to ensure accurate and reproducible feature detection. This chapter introduce...

Large-Scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.

MSMICA: computational metabolite identification in untargeted metabolomics by integrating MS, retention time, and biological evidence

MSMICA applies multiple pieces of evidence to substantially improve metabolite identification coverage and accuracy for known metabolites and enables greater metabolite identifications, expanded metabolic pathway coverage, and data harmonization.