| Literature DB >> 27575624 |
Hannes L Röst1,2, Timo Sachsenberg3,4, Stephan Aiche5, Chris Bielow6,7, Hendrik Weisser8, Fabian Aicheler3,4, Sandro Andreotti5, Hans-Christian Ehrlich5, Petra Gutenbrunner8, Erhan Kenar3,4,9, Xiao Liang10, Sven Nahnsen9, Lars Nilse11, Julianus Pfeuffer3,4, George Rosenberger1, Marc Rurik3,4, Uwe Schmitt12, Johannes Veit3,4, Mathias Walzer3,4, David Wojnar9, Witold E Wolski1,13, Oliver Schilling11,14, Jyoti S Choudhary8, Lars Malmström1,15, Ruedi Aebersold1,16, Knut Reinert5,17, Oliver Kohlbacher3,4,9,18,19.
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.Entities:
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Year: 2016 PMID： 27575624 DOI： 10.1038/nmeth.3959
Source DB: PubMed Journal: Nat Methods ISSN： 1548-7091 Impact factor: 28.547