Metabolomics Navigator Tools, strategies & workflow guidance for metabolomics

Data acquisition and instrument control

ViMMS

ViMMS simulates LC-MS/MS acquisition at scan level so researchers can prototype and compare fragmentation strategies.

LC-MSUntargeted metabolomicsPython packageOpen source
Access toolSuggest an update

Overview

ViMMS simulates LC-MS/MS acquisition at scan level so researchers can prototype and compare fragmentation strategies. It can generate virtual acquisitions from empirical or simulated chemical data and export simulated scans for downstream processing.

What can this tool do?

Spectral data reading and writing

Common uses

  • ViMMS simulates LC-MS/MS acquisition at scan level so researchers can prototype and compare fragmentation strategies.

Scientific fit

Primary function

Data acquisition and instrument control

Other functions

Workflow management and reproducibility

Analysis types

Untargeted metabolomics

Data compatibility

Inputs

Mass spectra, Feature or peak table

Outputs

Raw instrument data, Mass spectra

Input formats

Empirical LC-MS data or configured virtual chemicals/controllers

Output formats

Simulated acquisition results and mzML scans

Scope and considerations

Designed for

  • ViMMS simulates LC-MS/MS acquisition at scan level so researchers can prototype and compare fragmentation strategies.

Not designed for

  • Proof that a strategy's simulated performance will reproduce on every physical mass spectrometer.

Important requirements

  • The documented Python environment, empirical data or configured virtual chemicals and an acquisition controller; real-instrument experiments additionally require a compatible instrument API.

Considerations

  • Chemical models, scan timing and instrument assumptions constrain simulation realism. Validate promising strategies on the intended acquisition platform.

Access and documentation

Primary accessDocumentation

MIT source distribution. External datasets, dependent packages and any hosted routes retain their own terms; software operation was not tested.

License: MIT

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-batch3.md.

Core publications

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

  1. In Silico Optimization of Mass Spectrometry Fragmentation Strategies in Metabolomics. Metabolites (2019). doi:10.3390/metabo9100219
  2. ViMMS 2.0: A framework to develop, test and optimise fragmentation strategies in LC-MS metabolomics. Journal of Open Source Software (2022). doi:10.21105/joss.03990

Related tools

AutonoMSSimilar function · Automate ion-mobility metabolomic fingerprinting on a configured RapidFire system.BAGOSimilar function · BAGO is an open-source bioinformatics tool designed for the systematic optimization of LC gradient using the Bayesian optimization framework. It is particularly useful for optimizing LC gradients in LC-MS-based metabolomics, lipidomics, and exposomics.LipidCreatorSimilar function · Design targeted lipidomics assays and predicted fragment libraries for PRM and MRM experiments.MS2PlannerSimilar function · Plan precursor acquisition schedules from LC-MS survey features.

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 45 source-reviewed Enveda tool entries in third expansion batch

    View change · Entry at this revision

Full GitHub history