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Dataset . 2020
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Data sources: Datacite
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A data set for evaluation of peak detection methods

Authors: Müller, Erik; Huber, Carolin-Elisabeth; Beckers, Liza-Marie; Brack, Werner; Krauss, Martin; Schulze, Tobias;

A data set for evaluation of peak detection methods

Abstract

Nontargeted mass spectrometry (MS) has become an important method over the last years in the fields of metabolomics and environmental research. While more and more algorithms and workflows become available to process a large number of data sets nontargeted, there still exist few manually evaluated universal test data sets for refining and evaluating these methods. The first step of nontargeted screening, peak detection (and refinement of it) is arguably the most important step for nontargeted screening. However, the absence of a model data set makes it harder for researchers to evaluate peak detection methods. The data set was created from a previous real-world study, of which a subset was used to extract and manually classify ion chromatograms by three mass spectrometry experts.This data set is related to a Data Descriptor paper submitted to Metabolomics.

Keywords

extracted ion chromatograms, EIC, peak detection, peak picking, XIC, gap filling, mass spectrometry

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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