License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.11.6.1
URN: urn:nbn:de:0030-drops-155775
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Böcker, Sebastian ; Gundry, Rebekah ; Martens, Lennart ; Palmblad, Magnus
Weitere Beteiligte (Hrsg. etc.): Sebastian Böcker and Rebekah Gundry and Lennart Martens and Magnus Palmblad

Computational Proteomics (Dagstuhl Seminar 21271)

dagrep_v011_i006_p001_21271.pdf (3 MB)


This report documents the program and the outcomes of Dagstuhl Seminar 21271 "Computational Proteomics". The Seminar, which took place in a hybrid fashion with both local as well as online participation due to the COVID pandemic, was built around three topics: the rapid uptake of advanced machine learning in proteomics; computational challenges across the various rapidlly evolving approaches for structural and top-down proteomics; and the computational analysis of glycoproteomics data. These three topics were the focus of three corresponding breakout sessions, which ran in parallel throughout the seminar. A fourth breakout session was created during the seminar, on the specific topic of creating a Kaggle competition based on proteomics data.
The abstracts presented here first describe the three introduction talks, one for each topic. These talk abstracts are then followed by one abstract each per breakout session, documenting that breakout’s discussion and outcomes.
An Executive Summary is also provided, which details the overall seminar structure alongside the most important conclusions for the three topic-derived breakouts.

BibTeX - Entry

  author =	{B\"{o}cker, Sebastian and Gundry, Rebekah and Martens, Lennart and Palmblad, Magnus},
  title =	{{Computational Proteomics (Dagstuhl Seminar 21271)}},
  pages =	{1--13},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2021},
  volume =	{11},
  number =	{6},
  editor =	{B\"{o}cker, Sebastian and Gundry, Rebekah and Martens, Lennart and Palmblad, Magnus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-155775},
  doi =		{10.4230/DagRep.11.6.1},
  annote =	{Keywords: bioinformatics, computational mass spectrometry, machine learning, proteomics}

Keywords: bioinformatics, computational mass spectrometry, machine learning, proteomics
Collection: DagRep, Volume 11, Issue 6
Issue Date: 2021
Date of publication: 01.12.2021

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