Hannes Röst

Results Following the study design (Figure 1A; Table S1; STAR Methods), we collected samples across multiple continents during annual meetings of HUPO between 2016 and 2019. Sampling occurred at five sites, including a pilot cohort in Massachusetts (n = 31), followed by Taiwan (n = 106), Ireland (n = 113), and Florida (n = 87). An additional collection in California (n = 41) expanded the US cohort (Figures 1A, 1B, and S1A–S1E). Figure 1 Study design and demographics (A) Overview of hPOP study.

Abstract Despite decades of study, large parts of the mammalian metabolome remain unexplored1. Mass spectrometry-based metabolomics routinely detects thousands of small molecule-associated peaks in human tissues and biofluids, but typically only a small fraction of these can be identified, and structure elucidation of novel metabolites remains challenging2,3,4.

Abstract Tandem mass spectra capture fragmentation patterns that provide key structural information about molecules. Although mass spectrometry is applied in many areas, the vast majority of small molecules lack experimental reference spectra. For over 70 years, spectrum prediction has remained a key challenge in the field. Existing deep learning methods do not leverage global structure in the molecule, potentially resulting in difficulties when generalizing to new data.