The LIPID MAPS® Partial Spectra Database (Partial Spectra DB) is a specialized spectral database focused on lipids that are underrepresented in conventional lipidomics research because they are only partially structurally annotated.
By aggregating these spectra alongside expert-curated annotations and contextual information it facilitates the discovery and identification of novel lipid species that may otherwise remain overlooked.
While mammalian lipids dominate most analyses and their MS/MS fragmentation pattern is usually well described, many other lipids exist in other biological systems/organisms which are less investigated, where their structures are only partly-annotated. Similarly, epilipids —lipids modified by enzymatic or environmental processes are not always well annotated structurally. These lipids often feature distinctive substructure characteristics detectable by mass spectrometry, yet the spectral data obtained are insufficient to fully resolve the exact structural configuration. These spectra and associated metadata offer valuable insights into their biology and biochemistry and are essential for facilitating further research into their properties and their associations with health and disease.
The LIPID MAPS® Partial Spectra Database offers an interactive platform for browsing, searching, and downloading curated lipid spectra. Each entry includes detailed metadata and annotated fragment peaks, enabling users to explore spectral features with confidence. The database supports searches based on precursor ions, product ions, and neutral losses depending on user requirements. Spectra are available in open-access formats, allowing seamless integration into external tools and workflows for further computational or experimental investigation.
To support this growing field, we invite researchers to contribute their spectra of partially characterized lipids to the LIPID MAPS® Partial Spectra Database. Your submissions are a valuable resource that can help advance lipid discovery and foster collaborative progress across the lipidomics community, and you will be fully credited for your contribution. Please do so via the submission page .
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