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Dagstuhl-Seminar 15351

Computational Mass Spectrometry

( 23. Aug – 28. Aug, 2015 )

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Following in the steps of high-throughput sequencing, mass spectrometry (MS) has become a key analytical technique for large-scale studies of complex biological mixtures. MS-based experiments generate datasets of increasing complexity and size. Computational and statistical analysis of these datasets becomes a major bottleneck, which requires both methodological and practical solutions. We also hope to encourage discussions of emerging areas of research such as design and analysis of large, complex and heterogeneous datasets, which combine mass spectrometric and other experimental components for systems biology investigations. The participants will be able to suggest the details of these and other relevant topics, and each participant will be able to discuss multiple topics. While regular venues typically adhere to strict schedules and prepared remarks, Dagstuhl seminars devote a lot of time to spontaneous participant-driven interactions. The unique atmosphere of the castle fosters both technical discussions around a blackboard during the day, and more informal interactions over a glass of wine at night.

Dagstuhl seminars on computational mass spectrometry already have a rich history. Three previous seminars in 2008, 2010 and 2013 attracted many leading scientists of the field. The seminars resulted in joint papers, grant applications, and several community efforts with significant impact for the whole field. In particular, the stated goal of the 2013 seminar was to identify the grand challenges of the field. In contrast, in 2015 the organizers intend to explore more specific sub-areas and issues. We plan to include a series of overview talks by experts in experimental and computational mass spectrometry. We will expand the activities of the group beyond mass spectrometry-based proteomics, and devote more time to under-represented areas such as computational metabolomics.



Mass Spectrometry (MS) is an extremely flexible analytical technique, with applications ranging from crime lab investigations to testing to disease biomarkers in a clinic. The publication of the first human genome in 2001 was a key event that lead to the application of mass spectrometry to map out the human proteome, and later the human metabolome; i.e. all the biomolecules encoded in the genome that constitute biological function. The result was the creation of a tremendous amount of spectrometric data and a dearth of tools for data analysis, motivating the development of computational tools. The tool developers came from several expert domains; life scientists applying mass spectrometry built tools to automate their new workflows, analytical chemists and engineers developing the instruments built software to analyze devise measurements; network and database infrastructure professionals built resources for storing and sharing data in the cloud, and bioinformaticians and statisticians developed algorithms and statistical methods for data analysis. There is an ongoing need for the different disciplines to learn each other's languages, make tools interoperable, and establish common goals for development.


The seminar 'Computational Mass Spectrometry' is a follow-up seminar to the successful Dagstuhl seminars on `Computational Proteomics' and 'Computational Mass Spectrometry' (05471, 08101 and 14371).

The seminar aimed at bringing together scientists from a wide range of backgrounds and identify open issues and future research directions in computational mass spectrometry.


Already on the first days the seminar resulted in very lively discussions. The time allotted to the introductory talks had to be expanded to account for this. The discussions sparked off during the introductory talks led to the formation of several working groups. These groups formed and re-formed on demand, also based on discussion on the previous evenings. Section 5 documents the discussions and results in these groups through the notes taken. Some of these discussion (e.g., the one on false discovery rates) was of interest to all participants and took place as plenary discussions in the large lecture hall. Other discussions were more focussed and thus had a smaller number of participants.

Some of the discussion will certainly lead to joint research participants. A first tangible outcome is a joint paper already accepted in the Journal of Proteome Research (L. Gatto, K. D. Hansen, M. R. Hoopmann, H. Hermjakob, O. Kohlbacher, A.Beyer, "Testing and validation of computational methods for mass spectrometry," on benchmarking and validating computational methods for mass spectrometry. This working group developed conceptual ideas for benchmarking algorithms and implemented a web-based repository holding ( benchmark datasets that will hopefully make comparison of algorithms more transparent in the future. We are confident that the discussions of other working groups and the contacts made during the evening hours in Dagstuhl will result in many more collaborations and publications in the future.

The field of computational mass spectrometry is rapidly evolving. Participants identified a wide range of challenges arising from technological developments already at the horizon but also from the broadening on the application side. We thus intend to revisit the field in the coming years in a Dagstuhl seminar again, most likely organized by different leaders of the field in order to account for these upcoming changes.

Copyright Rudolf Aebersold, Oliver Kohlbacher, and Olga Vitek

  • Rudolf Aebersold (ETH Zürich, CH) [dblp]
  • Theodore Alexandrov (EMBL Heidelberg, DE) [dblp]
  • Naomi Altman (Pennsylvania State University - University Park, US) [dblp]
  • Nuno Bandeira (University of California - San Diego, US) [dblp]
  • Andreas Beyer (Universität Köln, DE) [dblp]
  • Sebastian Böcker (Universität Jena, DE) [dblp]
  • Robert Chalkley (UC - San Francisco, US)
  • Joshua Elias (Stanford University, US) [dblp]
  • Laurent Gatto (University of Cambridge, GB) [dblp]
  • Anne-Claude Gingras (University of Toronto, CA)
  • Matthias Gstaiger (ETH Zürich, CH)
  • Kasper Daniel Hansen (Johns Hopkins Univ. - Baltimore, US) [dblp]
  • Henning Hermjakob (European Bioinformatics Institute - Cambridge, GB) [dblp]
  • Michael Hoopmann (Institute for Systems Biology - Seattle, US) [dblp]
  • Lukas Käll (KTH - Royal Institute of Technology, SE) [dblp]
  • Oliver Kohlbacher (Universität Tübingen, DE) [dblp]
  • Bernhard Küster (TU München, DE) [dblp]
  • Kathryn Lilley (University of Cambridge, GB) [dblp]
  • Lennart Martens (Ghent University, BE) [dblp]
  • Sven Nahnsen (Universität Tübingen, DE) [dblp]
  • Pedro José Navarro Alvarez (Universität Mainz, DE)
  • Robert Ness (Purdue University, US)
  • Jonathon O'Brien (University of North Carolina - Chapel Hill, US)
  • Patrick Pedrioli (ETH Zürich, CH)
  • Knut Reinert (FU Berlin, DE) [dblp]
  • Lukas Reiter (Biognosys AG - Schlieren, CH) [dblp]
  • Bernhard Renard (Robert Koch Institut - Berlin, DE) [dblp]
  • Hannes Röst (Stanford University, US) [dblp]
  • Karen Sachs (Stanford University, US) [dblp]
  • Timo Sachsenberg (Universität Tübingen, DE) [dblp]
  • Albert Sickmann (ISAS - Dortmund, DE) [dblp]
  • Stephen Tate (SCIEX - Concord, CA) [dblp]
  • Stefan Tenzer (Universität Mainz, DE) [dblp]
  • Michael L. Tress (CNIO - Madrid, ES) [dblp]
  • Olga Vitek (Northeastern University - Boston, US) [dblp]
  • Christine Vogel (New York University, US) [dblp]
  • Susan T. Weintraub (The University of Texas Health Science Center, US)
  • David Wishart (University of Alberta - Edmonton, CA) [dblp]
  • Bernd Wollscheid (ETH Zürich, CH) [dblp]
  • Nicola Zamboni (ETH Zürich, CH) [dblp]

Verwandte Seminare
  • Dagstuhl-Seminar 05471: Computational Proteomics (2005-11-20 - 2005-11-25) (Details)
  • Dagstuhl-Seminar 08101: Computational Proteomics (2008-03-02 - 2008-03-07) (Details)
  • Dagstuhl-Seminar 13491: Computational Mass Spectrometry (2013-12-01 - 2013-12-06) (Details)
  • Dagstuhl-Seminar 17421: Computational Proteomics (2017-10-15 - 2017-10-20) (Details)
  • Dagstuhl-Seminar 19351: Computational Proteomics (2019-08-25 - 2019-08-30) (Details)
  • Dagstuhl-Seminar 21271: Computational Proteomics (2021-07-04 - 2021-07-09) (Details)
  • Dagstuhl-Seminar 23301: Computational Proteomics (2023-07-23 - 2023-07-28) (Details)

  • bioinformatics

  • bioinformatics
  • computational mass spectrometry
  • proteomics
  • metabolomics
  • glycomics