Computational Metabolomics: Towards Molecules, Models, and their Meaning (Dagstuhl Seminar 24181)

Authors Timothy M. D. Ebbels, Soha Hassoun, Ewy A. Mathé, Justin J. J. van der Hooft, Haley Chatelaine and all authors of the abstracts in this report



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Author Details

Timothy M. D. Ebbels
  • Imperial College London, GB
Soha Hassoun
  • Tufts University - Medford, US
Ewy A. Mathé
  • National Institutes of Health - Bethesda, US
Justin J. J. van der Hooft
  • Wageningen University and Research, NL
Haley Chatelaine
  • NCATS - Bethesda, US
and all authors of the abstracts in this report

Cite AsGet BibTex

Timothy M. D. Ebbels, Soha Hassoun, Ewy A. Mathé, Justin J. J. van der Hooft, and Haley Chatelaine. Computational Metabolomics: Towards Molecules, Models, and their Meaning (Dagstuhl Seminar 24181). In Dagstuhl Reports, Volume 14, Issue 4, pp. 124-141, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/DagRep.14.4.124

Abstract

Dagstuhl Seminar "Computational Metabolomics: Towards Molecules, Models, and their Meaning," (24181) is the fifth edition of the Computational Metabolomics seminars. Experts in fields ranging from cheminformatics, computer science, bioinformatics, analytical chemistry, and epidemiology attended to address the current state and future directions of this multi-disciplinary field. Specific topics of discussion were decided by participants but largely revolved around the seminar’s titular themes of molecules (i.e., utilizing and annotating individual metabolites for use in models), models (i.e., generating systems from which to derive meaning), and meaning (i.e., deriving actionable insights to further understanding of biological systems). New to this seminar, topics of education and training, as well as the use of large language models to enhance access to resources, were also discussed. Participants identified community needs for a balance of standardization and flexibility in realms of repository-scale data deposition and analysis, spectral library generation, automation best practices, and biological pathway interpretation. Participants also identified a number of action items toward these ends, fostering international collaborations among them. For example, one topic evolved around creating a benchmarking dataset for structure annotation based on MS/MS spectral data. Discussions represented balanced perspectives, thanks to varied session facilitators and active participation of all members. The report contained herein reflects highlights of each session, including informal evening sessions and ideas for future directions.

Subject Classification

ACM Subject Classification
  • Applied computing → Life and medical sciences
Keywords
  • bioinformatics
  • cheminformatics
  • data integration
  • machine learning
  • mass spectrometry
  • metabolite identification
  • metabolomics
  • pathway analysis
  • repository-scale analysis
  • training and education

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