Morgan W. Panitchpakdi

The paper expands a bile acid and steroidal MS/MS spectral library across three repositories, capturing diverse structures and providing a resource for classifying unknown spectra.

The paper assesses how common storage conditions and additives affect urinary metabolite profiles, finding minimal impact from storage but significant changes from a DNA-stabilizer.

The paper creates a suspect spectral library for untargeted metabolomics by propagating annotations from public MS/MS spectra to improve interpretation of unannotated spectra.

The paper introduces Ion Identity Molecular Networking to connect ion species of the same molecule, improving network connectivity and annotation.

The paper introduces a web-based tool for collaborative analysis of mass spectrometry data, enabling remote inspection, visualization, and analysis of private and public datasets.

The paper develops a machine learning workflow for auto-deconvolution of GC-MS data within GNPS, enabling molecular networking and applications in breathomics and volatilome mapping.

The paper develops ReDU, a tool for discovering and re-analyzing metabolomics data in GNPS, following FAIR principles.

This paper expands the interpretability of human metabolomes by using food-based annotations, increasing the fraction of molecular features understood 7-fold.

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

MASST enables querying of public small-molecule tandem MS data to discover molecular relationships in metabolomics and natural product datasets.

This paper uses untargeted mass spectrometry to analyze chemical changes in foods during preparation and storage, finding that some processes alter molecular composition while others primarily involve extraction.