Vanessa V. Phelan

The Everything Bagel feature finder automates metabolomics data processing, achieving comparable or better performance than existing methods with significantly reduced computational time.

This paper introduces MT-GEM and STEP to predict discrete structural transformations in metabolites from MS/MS spectra, achieving significant improvements over existing methods.

This paper removes iron from commercial mucins to improve the accuracy of synthetic microbiota models in cystic fibrosis.

ModiFinder localizes structural modification sites in small molecules by aligning MS/MS spectra of known and unknown compounds.

MassQL, an open-source query language, lets users search raw mass spectrometry data from any vendor for isotope, fragmentation and neutral-loss patterns, from one file to entire public repositories.

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 introduces FBMN, a method for improving molecular networking by enhancing quantitative analysis and isomer distinction using feature detection and alignment tools in the GNPS platform.