Alan K. Jarmusch

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

This study identifies metabolic and exosomal mechanisms of neuroprotection in hibernating thirteen-lined ground squirrels following optic nerve injury.

This study tests if inhibiting succinate oxidation with dimethyl malonate protects neurons after optic nerve injury but finds it impairs phagocytosis and fails to reduce inflammation.

The paper identifies BilV, a novel enzyme that works with BilR to reduce bilirubin to urobilinogen, and shows its distribution varies across vertebrate gut microbiomes.

The paper introduces a collaborative platform for curating microbial metabolite knowledge to enhance metabolomics data interpretation.

This paper describes a protocol using MetVAE to construct molecular networks from metabolomics data, identifying lipid correlations in a mouse model.

This study shows pericyte-tumor interactions promote metastatic tumor cell dormancy via PIEZO1-mediated lysophospholipid transfer, enhancing persistence and relapse risk.

The paper develops a drug exposure resource from untargeted metabolomics data to identify medications without clinical records.

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

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 uses a random forest classifier to predict which drugs are detectable on skin using metabolomics, finding that nervous system drugs are more likely to be detected.

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 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.

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.