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dc.contributor.author
Ebbels, Timothy M.D.
dc.contributor.author
van der Hooft, Justin J.J.
dc.contributor.author
Chatelaine, Haley
dc.contributor.author
Broeckling, Corey
dc.contributor.author
Zamboni, Nicola
dc.contributor.author
Hassoun, Soha
dc.contributor.author
Mathé, Ewy A.
dc.date.accessioned
2023-04-12T09:21:41Z
dc.date.available
2023-04-12T03:20:21Z
dc.date.available
2023-04-12T09:21:41Z
dc.date.issued
2023-06
dc.identifier.issn
1367-5931
dc.identifier.issn
1879-0402
dc.identifier.other
10.1016/j.cbpa.2023.102288
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/607327
dc.identifier.doi
10.3929/ethz-b-000607327
dc.description.abstract
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines. The field continues to expand as modern instrumentation produces datasets with increasing complexity, resolution, and sensitivity. These datasets must be processed, annotated, modeled, and interpreted to enable biological insight. Techniques for visualization, integration (within or between omics), and interpretation of metabolomics data have evolved along with innovation in the databases and knowledge resources required to aid understanding. In this review, we highlight recent advances in the field and reflect on opportunities and innovations in response to the most pressing challenges. This review was compiled from discussions from the 2022 Dagstuhl seminar entitled “Computational Metabolomics: From Spectra to Knowledge”.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Metabolomics
en_US
dc.subject
Multi-omics
en_US
dc.subject
Machine learning
en_US
dc.subject
Metabolite identification
en_US
dc.subject
Cheminformatics
en_US
dc.subject
Chemometrics
en_US
dc.subject
Visualization
en_US
dc.subject
Benchmarking
en_US
dc.subject
Small molecules
en_US
dc.title
Recent advances in mass spectrometry-based computational metabolomics
en_US
dc.type
Review Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2023-03-24
ethz.journal.title
Current Opinion in Chemical Biology
ethz.journal.volume
74
en_US
ethz.journal.abbreviated
Curr. opin. chem. biol.
ethz.pages.start
102288
en_US
ethz.size
10 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02538 - Institut für Molekulare Systembiologie / Institute for Molecular Systems Biology::08839 - Zamboni, Nicola (Tit.-Prof.)
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02538 - Institut für Molekulare Systembiologie / Institute for Molecular Systems Biology::08839 - Zamboni, Nicola (Tit.-Prof.)
ethz.date.deposited
2023-04-12T03:20:22Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2023-04-12T09:21:43Z
ethz.rosetta.lastUpdated
2024-02-02T21:35:30Z
ethz.rosetta.versionExported
true
ethz.COinS
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