Speaker Profile
Ph.D., Sr. Director, R&D,
Biography
Ethan Stancliffe leads the development of MassID, a cloud-based untargeted metabolomics and exposomics platform that brings probabilistic metabolite identification, deep-learningbased peak detection, and comprehensive noise filtration to large-scale LCMS analysis. His work focuses on solving core challenges in metabolomics like data noise, chemical degeneracy, and unreliable metabolite identification through machine-learning and Bayesian inference. He developed PeakDetective and DecoID2, enabling high-confidence identification across tens of thousands of mass spectral features and FDR-controlled metabolomics. His team has demonstrated near-complete annotation of human plasma datasets and scalable workflows for population-level multi-omics studies, including exposure profiling, pathway analysis, and disease mechanism discovery. Ethans innovations advance the reliability and interpretability of metabolomics, exposomics, and multi-omic integration for biomedical research, environmental health, and precision medicine.
Talk
Integrated Mass Spectrometry-based Multi-Omics for Population-scale Studies
MassID delivers probabilistic, FDR-controlled metabolite identification and ultra-high-coverage LCMS analysis for exposomics and multi-omics research. This talk will demonstrate how deep-learning peak detection, noise filtration, and Bayesian identification unify small-molecule discovery with targeted and untargeted exposomics to reveal chemical exposures, metabolic disruptions, and disease-relevant pathways at population scale.
Spatial Showcase:
Panome Bio
Panome Bio is a CRO that provides scalable, high-resolution metabolomics, exposomics, and phosphoproteomics services powered by cloud-based analytics, deep-learning signal detection, and probabilistic metabolite identification. Panome enables comprehensive small-molecule discovery, environmental exposure profiling, and multi-omic integration for biobanks, clinical research, and population-scale health studies.
