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Computational metabolomics at scale: from open data to insight.

Ewy A Mathé·Justin Jj van der Hooft·Haley Chatelaine·Louis-Félix Nothias·Stacey N Reinke·Juan Antonio Vizcaíno·Egon L Willighagen·Timothy Md Ebbels·Soha Hassoun
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Abstract

Metabolomics data are currently generated at scale thanks to the evolution of technologies that have led to marked improvements in the number of metabolites detected, spanning all chemical classes. These data are increasingly submitted to public repositories for data reuse, integration, and interpretation. Despite the availability of public resources and associated computational tools, the field still lacks a widely adopted, consistent data and analytics infrastructure capable of transforming this wealth of information into scientific insight. Indeed, the metabolomics field is just now scratching the surface of being able to harness the power of new computational technologies. In this review, we summarize discussions from the "Dagstuhl-Seminar 24181 Computational Metabolomics: Towards Molecules, Models, and their Meaning" with a focus on public data availability, open data standards, data and knowledge integration, and education. Our goal is to raise awareness and adoption of the latest open science resources while highlighting key areas needing further development.

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Ewy A Mathé, Justin Jj van der Hooft, Haley Chatelaine, Louis-Félix Nothias, Stacey N Reinke, Juan Antonio Vizcaíno, Egon L Willighagen, Timothy Md Ebbels, Soha Hassoun. 2026-08-05. Computational metabolomics at scale: from open data to insight.. https://doi.org/10.1016/j.copbio.2026.103557

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