A sulfatide-centered ultra-high-resolution magnetic resonance MALDI imaging benchmark dataset for MS1-based lipid annotation tools.

ABSTRACT:

Background

Spatial omics techniques are indispensable for studying complex biological systems and for the discovery of spatial biomarkers. While several current matrix-assisted laser desorption/ionization mass spectrometry imaging (MSI) instruments are capable of localizing numerous metabolites at high spatial and spectral resolution, most MSI data are acquired at the MS1 level only. Assigning molecular identities based on MS1 data presents significant analytical and computational challenges, as the inherent limitations of MS1 data preclude confident annotations beyond the sum formula level.

Results

To enable future advancements of computational lipid annotation tools, well-characterized benchmark-or ground-truth-datasets are crucial, which exceed the scope of synthetic data

SUBMITTER: Gruber L 

PROVIDER: S-EPMC12766628 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature