Overview
Spec2Vec adapts Word2Vec to spectral data, representing spectra through learned relationships between fragment patterns rather than only direct peak overlap.
What can this tool do?
Common uses
- Rank related spectra for exploratory analysis.
- Compare embedding-based and conventional spectral similarity.
Scientific fit
Primary function
Spectral processing and comparison
Data compatibility
Inputs
Mass spectra
Outputs
Statistical results
Input formats
MGF
Output formats
Other, Spectral embeddings and similarity scores
Scope and considerations
Designed for
- Rank related spectra for exploratory analysis.
Not designed for
- Assigning a unique structure from the embedding score alone.
Important requirements
- Python, processed spectra and a pretrained or locally trained Word2Vec model.
Considerations
- Model coverage matters: peaks absent from training can weaken a score. Record the model and missing-peak threshold.
Access and documentation
Open-source software; use the official installation, license and citation guidance for the selected release.
Evidence and review
Documentation-based editorial review on 7 September 2026. Scope and limitations summarize the linked official sources; software execution and developer verification were not assessed.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- Huber F, Ridder L, Verhoeven S, et al. Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships. PLoS Comput Biol 17, e1008724 (2021). doi:10.1371/journal.pcbi.1008724
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-09-08 · Entry update
Audit core publications across existing tools
View change · Entry at this revision - 2026-09-07 · First committed entry
Add 50 documented metabolomics resources
View change · Entry at this revision