Reference : Computational Metabolomics: From Cheminformatics to Machine Learning (Dagstuhl Semina...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Physical, chemical, mathematical & earth Sciences : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/44043
Computational Metabolomics: From Cheminformatics to Machine Learning (Dagstuhl Seminar 20051)
English
Böcker, Sebastian [> >]
Broeckling, Corey [> >]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Zamboni, Nicola [> >]
2020
Dagstuhl Reports
No
Yes
International
Dagstuhl Seminar 20051: Computational Metabolomics
26-01-2020 to 31-01-2020
Schloss Dagstuhl-Leibniz-Zentrum für Informatik
[en] bioinformatics ; machine learning ; computational metabolomics ; computational mass spectrometry ; chemoinformatics
[en] Dagstuhl Seminar 20051 on Computational Metabolomics is the third edition of seminars onthis topic and focused on Cheminformatics and Machine Learning. With the advent of higherprecision instrumentation, application of metabolomics to a wider variety of small molecules, andever increasing amounts of raw and processed data available, developments in cheminformaticsand machine learning are sorely needed to facilitate interoperability and leverage further insightsfrom these data. Following on from Seminars 17491 and 15492, this edition convened bothexperimental and computational experts, many of whom had attended the previous sessions andbrought much-valued perspective to the week’s proceedings and discussions. Throughout theweek, participants first debated on what topics to discuss in detail, before dispersing into smaller,focused working groups for more in-depth discussions. This dynamic format was found to bemost productive and ensured active engagement amongst the participants. The abstracts inthis report reflect these working group discussions, in addition to summarising several informalevening sessions. Action points to follow-up on after the seminar were also discussed, includingfuture workshops and possibly another Dagstuhl seminar in late 2021 or 2022.
http://hdl.handle.net/10993/44043
10.4230/DagRep.10.1.144
FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics to Identify Unknown Chemicals and their Effects > 01/10/2018 > 30/09/2023 > 2018

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