Bishoy Wadie

HT SpaceM is a high-throughput single-cell metabolomics method that detects small molecules with high reproducibility and identifies cell-type markers and metabolic pathways in diverse cell lines.

The paper introduces S2IsoMEr and METASPACE tools to handle molecular ambiguity in spatial and single-cell metabolomics through bootstrapping for enrichment analysis.

METASPACE-ML improves metabolite annotation in imaging mass spectrometry by using machine learning, achieving higher precision and throughput than a rule-based method.

The paper identifies human linear motifs by analyzing viral protein interactions, finding 8,400 motif instances with 105 supported by multiple filters.