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Version 2. F1000Res. 2017 Sep 6 [revised 2017 Oct 30];6. pii: ELIXIR-1649. doi: 10.12688/f1000research.12342.2. eCollection 2017.

The future of metabolomics in ELIXIR.

Author information

1
ELIXIR-NL, Dutch Techcentre for Life Sciences, Utrecht, 3503 RM, Netherlands.
2
Netherlands Metabolomics Center, Leiden, 2333 CC, Netherlands.
3
ADReM, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, 2020, Belgium.
4
ELIXIR-FR, French Institute of Bioinformatics, Gif-sur-Yvette, F-91198, France.
5
Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain.
6
School of Biosciences, Phenome Centre Birmingham and Birmingham Metabolomics Training Centre, University of Birmingham, Birmingham, B15 2TT, UK.
7
Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK.
8
INRA, UNH, Human Nutrition Unit, PFEM, Metabolism Exploration Platform, MetaboHUB-Clermont, Clermont Auvergne University, Clermont-Ferrand, F-63000, France.
9
Oxford e-Research Centre, Engineering Science Department, University of Oxford, Oxford, OX1 3QG, UK.
10
Leiden Academic Centre for Drug Research, Leiden University, Leiden, 2300 RA, Netherlands.
11
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK.
12
Centro Nacional Investigaciones Cardiovasculares, Madrid, 28029, Spain.
13
CIBER de Enfermedades Respiratorias, Madrid, 28029 , Spain.
14
ELIXIR Hub, Cambridge, CB10 1SD, UK.
15
Toxalim, UMR 1331, Université de Toulouse, Toulouse, F-31300, France.
16
Metabolic Engineering and Systems Biology Laboratory, Institute of Chemical Engineering Sciences, Foundation for Research & Technology - Hellas (FORTH/ICE-HT), Patras, GR-26504, Greece.
17
Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, 72076, Germany.
18
Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany.
19
Center for Bioinformatics, University of Tübingen, Tübingen, 72076, Germany.
20
The Centre of Excellence in Neural and Behavioural Sciences, Tallinn, Tallinn, 10120, Estonia.
21
School of Natural Sciences and Health, Tallinn University, 10120, 10120, Estonia.
22
Department of Medical Sciences, Uppsala University, Uppsala, 752 36, Sweden.
23
UPMC, CNRS, FR2424, ABiMS, Station Biologique, Roscoff, F-29680, France.
24
Department of General Biology, School of Medicine, University of Patras, Patras, GR-26504, Greece.
25
Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, 06120, Germany.
26
BSRC "Alexander Fleming", Athens, GR-16672, Greece.
27
Magnetic Resonance Center, Interuniversity Consortium for Magnetic Resonance on MetalloProteins, University of Florence, Florence, 50121, Italy.
28
Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, L-4367, Luxembourg.
29
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, 752 36, Sweden.
30
CEA, LIST, Laboratory for Data Analysis and Systems' Intelligence, MetaboHUB, Gif-sur-Yvette, F-91191, France.
31
Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, NL-6200, Netherlands.
32
CRS4, Data Intensive Computing Group, Ed.1 POLARIS, Pula, 09010, Italy.
33
Friedrich-Schiller-University, Jena, 07743, Germany.

Abstract

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

KEYWORDS:

bioinformatics infrastructure; cloud computing; computational workflows; data standards; databases; metabolomics; multi-omics approaches; training

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