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OpenMS: a flexible open-source software platform for mass spectrometry data analysis

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Official URL:https://doi.org/10.1038/nmeth.3959
PubMed:View item in PubMed
Creators Name:Roest, H.L. and Sachsenberg, T. and Aiche, S. and Bielow, C. and Weisser, H. and Aicheler, F. and Andreotti, S. and Ehrlich, H.C. and Gutenbrunner, P. and Kenar, E. and Liang, X. and Nahnsen, S. and Nilse, L. and Pfeuffer, J. and Rosenberger, G. and Rurik, M. and Schmitt, U. and Veit, J. and Walzer, M. and Wojnar, D. and Wolski, W.E. and Schilling, O. and Choudhary, J.S. and Malmstroem, L. and Aebersold, R. and Reinert, K. and Kohlbacher, O.
Journal Title:Nature Methods
Journal Abbreviation:Nat Methods
Volume:13
Number:9
Page Range:741-748
Date:September 2016
Keywords:Aging, Automatic Data Processing, Blood Proteins, Computational Biology, Mass Spectrometry, Molecular Sequence Annotation, Proteogenomics, Proteomics, Software, Workflow
Abstract:High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.
ISSN:1548-7091
Publisher:Nature Publishing Group (U.S.A.)
Item Type:Article

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