Computational Metabolomics Software Tools from 2021 to 2025

746 mass spectrometry- and spectroscopy-based metabolomics tools across 37 categories are aggregated in this curated database. It tracks structural shifts in the field from 2021 to 2025, including a 2.4-fold increase in machine learning adoption and the rise of Python as the dominant programming language. The dataset was created by Daniel Domingo-Fernández and last updated in May 2026.

Use Cases

• Analyze trends in machine learning adoption for metabolomics based on reported tool categories and ML usage percentages.
• Compare the prevalence of programming languages like Python and R over time based on the described inflection point in 2023.
• Study the evolution of metabolite annotation strategies from library matching to de novo structure generation based on the described dominant strategy shifts.
• Investigate the growth of transformer architectures and large language models in metabolomics based on the reported emergence of such tools in 2025.

Strengths

• Aggregates 746 distinct tools, providing a broad overview of the software landscape.
• Tracks a 2.4-fold increase in machine learning adoption from 2021 to 2025.
• Categorizes tools across 37 functional categories, with annotation being the largest at 16.8%.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale statistical analysis.

Provenance

Source

figshare

Collection Method

Curated aggregation from the metabolomics research community, likely from literature and software repositories.

Time Range

2021–2025

Freshness

Last updated 2026-05-31 14:03:21; freshness should be verified.