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Metabolite annotation and identification

MIST-CF

A machine-learning tool for ranking molecular formula and adduct assignments directly from MS/MS spectra using a transformer-based model without requiring spectral-library matching.

Platform-independentUntargeted metabolomicsPython packageCommand lineOpen source
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Overview

MIST-CF ranks molecular-formula and adduct candidates using precursor mass and tandem spectral evidence with a formula-transformer model. The documented workflow enumerates formulas using SIRIUS decomposition and then scores them without constructing fragmentation trees.

What can this tool do?

Molecular-formula prediction

Common uses

  • Rank chemical-formula and adduct candidates for unknown MS/MS spectra.
  • Apply pretrained models to public natural-product or CASMI-style spectra.

Scientific fit

Primary function

Metabolite annotation and identification

Other functions

Machine learning and prediction

Analysis types

Untargeted metabolomics

Data compatibility

Inputs

Mass spectra

Outputs

Compound list or annotations

Input formats

MGF

Output formats

CSV or TSV

Scope and considerations

Designed for

  • De novo formula and adduct ranking from small-molecule MS/MS spectra.

Not designed for

  • Full molecular-structure identification or an established negative-ion workflow.

Important requirements

  • Python environment, pretrained weights and positive-ion MS/MS input. The supplied workflow requires SIRIUS decomposition; an interactive example also supports user-specified candidates.

Considerations

  • Formula/adduct rankings remain hypotheses and depend on instrument and training-domain coverage. Public and NIST-trained models should not be treated as interchangeable.

Access and documentation

Primary accessDocumentation

MIT-licensed implementation. A public NPLIB1-trained model is linked; NIST20-trained model access is separately restricted to users with a NIST license and is not equivalent to the public checkpoint.

License: MIT

Evidence and review

Enveda intake rechecked against official README/documentation, repository access terms and primary publication metadata on 2026-10-27. Editorial source review only; no software execution or independent benchmarking. See docs/enveda-expansion-review-2026-10-27.md.

Core publications

Resource papers, direct updates and tool-specific methods. Selection policy.

  1. MIST-CF: Chemical Formula Inference from Tandem Mass Spectra. Journal of Chemical Information and Modeling 64, 2421–2431 (2024; first online 2023). doi:10.1021/acs.jcim.3c01082

Related tools

BAMSimilar function · BAM generates and ranks structural candidates for suspect metabolites by applying biotransformation rules to known anchor structures.BUDDY / msbuddySimilar function · Generate and rank molecular formula annotations for small-molecule mass-spectrometry queries.CANOPUSSimilar function · A SIRIUS-integrated machine-learning method and webservice for predicting compound classes directly from high-resolution MS/MS data without requiring an exact database structure match.CFM-IDSimilar function · Predict tandem mass spectra, annotate fragments and rank candidate structures for small molecules.

Entry history

Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.

  1. 2026-10-27 · First committed entry

    Add 27 source-reviewed tools from Enveda intake

    View change · Entry at this revision

Full GitHub history