Overview
LipiDetective predicts molecular lipid species in standardized shorthand notation from tandem spectra using a transformer model. It offers model training with prepared data and inference for supported spectra, providing a complementary source of annotation evidence.
What can this tool do?
Common uses
- A deep-learning framework for identifying molecular lipid species from tandem mass spectra.
Scientific fit
Primary function
Metabolite annotation and identification
Other functions
Machine learning and prediction
Analysis types
Lipidomics
Data compatibility
Inputs
Mass spectra
Outputs
Compound list or annotations
Input formats
mzML spectra for prediction; HDF5 data and YAML for training
Output formats
Predicted lipid shorthand annotations and model-dependent scores
Scope and considerations
Designed for
- A deep-learning framework for identifying molecular lipid species from tandem mass spectra.
Not designed for
- Confirming double-bond positions or stereochemistry not resolved by the model, or accepting every generated lipid name without checking precursor compatibility.
Important requirements
- Python environment, YAML configuration and trained checkpoint; the documented training route uses HDF5 data and prediction uses mzML files.
Considerations
- Training-set lipid/adduct and instrument coverage affect performance. Inspect predictions against precursor mass and diagnostic fragments; the current paper discusses training bias and missing hard precursor-mass constraints.
Access and documentation
BSD-3-Clause source distribution. External datasets, dependent packages and any hosted routes retain their own terms; software operation was not tested.
License: BSD-3-Clause
Evidence and review
Enveda intake rechecked against official repository documentation, package/license metadata and primary publication identity on 2026-10-27. Editorial source review only; no software execution or independent benchmark. See docs/enveda-expansion-review-2026-10-27-batch2.md.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- LipiDetective: a deep learning model for the identification of molecular lipid species in tandem mass spectra. Briefings in Bioinformatics (2026). doi:10.1093/bib/bbag378
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-27 · First committed entry
Add 24 reviewed Enveda tools in a separate second batch
View change · Entry at this revision