Haoqi Nina Zhao

Polyethylene glycol in human biofluids can mark drug exposure rather than contamination; it is oxidized to acid metabolites and appears in 2.3% of public metabolomics files.

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

The paper develops an agentic AI system using LLMs and domain tools to hypothesize and validate structures of unknown drug metabolites from mass spectrometry data.

The paper identifies alkamines as a previously hidden class of metabolites formed via reductive amination, revealing significant gaps in metabolomics and drug metabolism understanding.

The paper identifies microbial bile acid conjugation as a drug-activating function for 5-ASA, revealing its therapeutic relevance through metabolomics analysis.

This study maps conjugated metabolites by analyzing MS/MS spectra from public repositories, identifying potential conjugation events and providing a resource for structural discovery.

The paper introduces microbiomeMASST, a metadata network graph linking metabolites across datasets, enabling cross-study analysis of microbial metabolites and their biological context.

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

The paper uses synthetic multiplexing to annotate uncharacterized metabolites, identifying ibuprofen-carnitine as a metabolite linked to muscle toxicity.

The paper creates a spectral library of N-acyl lipids from metabolomics data, identifies novel compounds, and links them to health conditions like HIV and cognitive impairment.

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

The paper curates LC-MS/MS data from plant extracts to create a taxonomically focused database for exploring plant-derived molecules.

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.