Workflows for automated downstream data analysis and visualization in large‐scale computational mass spectrometry

MS‐based proteomics and metabolomics are rapidly evolving research fields driven by the development of novel instruments, experimental approaches, and analysis methods. Monolithic analysis tools perform well on single tasks but lack the flexibility to cope with the constantly changing requirements and experimental setups. Workflow systems, which combine small processing tools into complex analysis pipelines, allow custom‐tailored and flexible data‐processing workflows that can be published or shared with collaborators. In this article, we present the integration of established tools for computational MS from the open‐source software framework OpenMS into the workflow engine Konstanz Information Miner (KNIME) for the analysis of large datasets and production of high‐quality visualizations. We provide example workflows to demonstrate combined data processing and visualization for three diverse tasks in computational MS: isobaric mass tag based quantitation in complex experimental setups, label‐free quantitation and identification of metabolites, and quality control for proteomics experiments.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Workflows for automated downstream data analysis and visualization in large‐scale computational mass spectrometry ; volume:15 ; number:8 ; year:2015 ; pages:1443-1447 ; extent:5
Proteomics ; 15, Heft 8 (2015), 1443-1447 (gesamt 5)

Creator
Aiche, Stephan
Sachsenberg, Timo
Kenar, Erhan
Walzer, Mathias
Wiswedel, Bernd
Kristl, Theresa
Boyles, Matthew
Duschl, Albert
Huber, Christian G.
Berthold, Michael
Reinert, Knut
Kohlbacher, Oliver

DOI
10.1002/pmic.201400391
URN
urn:nbn:de:101:1-2022112507275385353251
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:26 AM CEST

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