TY - JOUR
T1 - Computational metabolomics at scale
T2 - from open data to insight
AU - Mathé, Ewy A.
AU - van der Hooft, Justin J.J.
AU - Chatelaine, Haley
AU - Nothias, Louis Félix
AU - Reinke, Stacey N.
AU - Vizcaíno, Juan Antonio
AU - Willighagen, Egon L.
AU - Ebbels, Timothy M.D.
AU - Hassoun, Soha
N1 - Funding Information:
This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH). This work was supported in part by the intramural program at the National Center for Advancing Translational Sciences (ZIA TR000547 ). SH was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM148219 . The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services. T.M.D.E. acknowledges partial support from the United Kingdom Research and Innovation (UKRI) Biotechnology and Biological Sciences Research Council (grants BB/T007974/1 , BB/W002345/1 ), and European Union projects BiA CEM (grant EC101079370 , UKRI 10050966 ) and HUMAN (grant EC101073062 , UKRI EP/X035840/1 ). L.-F.N acknowledges support by the French National Research Agency (ANR) with the reference numbers ANR-15-IDEX-01 and ANR-22-CPJ2-0048-01 . J.J.J.vdH. acknowledges funding from the Netherlands Organization for Scientific Research (NWO) KIC Microbiome Mission grant KICH1.LWV04.21.013 and the European Union\u2019s Horizon Europe programme under the Marie Sk\u0142odowska-Curie grant agreement No 101072485 (MAGic-MOLFUN). J.A.V. acknowledges funding from EMBL core funding, BBSRC (grant number BB/W000156/1 ), and the Chan Zuckerberg Initiative (grant number 2024-350548 ) (also added in the manuscript).
Publisher Copyright:
© 2026 .
PY - 2026/10/1
Y1 - 2026/10/1
N2 - 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.
AB - 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.
U2 - 10.1016/j.copbio.2026.103557
DO - 10.1016/j.copbio.2026.103557
M3 - (Systematic) Review article
SN - 0958-1669
VL - 101
JO - Current Opinion in Biotechnology
JF - Current Opinion in Biotechnology
M1 - 103557
ER -