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eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows


Kiefer, P; Schmitt, U; Vorholt, J A (2013). eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows. Bioinformatics, 29(7):963-964.

Abstract

The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS.

Abstract

The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS.

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Item Type:Journal Article, refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > BattleX
Special Collections > SystemsX.ch > Research, Technology and Development Projects
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Life Sciences > Biochemistry
Life Sciences > Molecular Biology
Physical Sciences > Computer Science Applications
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Computational Mathematics
Language:English
Date:2013
Deposited On:17 Sep 2013 17:54
Last Modified:30 Jul 2020 09:51
Publisher:Oxford University Press
ISSN:1367-4803
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btt080

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