Lívia S. Eberlin

This study demonstrates that MasSpec Pen technology can rapidly identify bacterial species in clinical isolates and specimens with high accuracy using molecular profiles of metabolites and lipids.

The paper introduces MAGPIE, a framework for integrating spatial transcriptomics, metabolomics, and tissue morphology data, demonstrating its application in studying drug-induced pulmonary fibrosis.

The paper integrates spatial metabolomics and spatial transcriptomics on cancer tissues to identify gene-metabolite correlations.

The paper evaluates spatial metabolomics protocols and technologies, showing extensive metabolite coverage and comparable results across imaging MS methods.

The paper introduces an aggregated molecular phenotype (AMP) scoring system to visualize and classify molecular changes in mass spectrometry imaging data with high accuracy.

An open-source cloud engine annotates imaging mass spectrometry data at controlled false discovery rate; publicly shared results reached over 3200 datasets and 6 million metabolite images by January 2019.