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MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data

Overview of attention for article published in Metabolomics, October 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

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5 tweeters

Readers on

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70 Mendeley
Title
MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data
Published in
Metabolomics, October 2014
DOI 10.1007/s11306-014-0734-y
Pubmed ID
Authors

Alexander Kaever, Manuel Landesfeind, Kirstin Feussner, Alina Mosblech, Ingo Heilmann, Burkhard Morgenstern, Ivo Feussner, Peter Meinicke

Abstract

A central aim in the evaluation of non-targeted metabolomics data is the detection of intensity patterns that differ between experimental conditions as well as the identification of the underlying metabolites and their association with metabolic pathways. In this context, the identification of metabolites based on non-targeted mass spectrometry data is a major bottleneck. In many applications, this identification needs to be guided by expert knowledge and interactive tools for exploratory data analysis can significantly support this process. Additionally, the integration of data from other omics platforms, such as DNA microarray-based transcriptomics, can provide valuable hints and thereby facilitate the identification of metabolites via the reconstruction of related metabolic pathways. We here introduce the MarVis-Pathway tool, which allows the user to identify metabolites by annotation of pathways from cross-omics data. The analysis is supported by an extensive framework for pathway enrichment and meta-analysis. The tool allows the mapping of data set features by ID, name, and accurate mass, and can incorporate information from adduct and isotope correction of mass spectrometry data. MarVis-Pathway was integrated in the MarVis-Suite (http://marvis.gobics.de), which features the seamless highly interactive filtering, combination, clustering, and visualization of omics data sets. The functionality of the new software tool is illustrated using combined mass spectrometry and DNA microarray data. This application confirms jasmonate biosynthesis as important metabolic pathway that is upregulated during the wound response of Arabidopsis plants.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Brazil 2 3%
Spain 1 1%
South Africa 1 1%
Netherlands 1 1%
Unknown 63 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 31%
Student > Ph. D. Student 16 23%
Student > Bachelor 9 13%
Student > Master 8 11%
Professor > Associate Professor 4 6%
Other 11 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 46%
Biochemistry, Genetics and Molecular Biology 14 20%
Chemistry 8 11%
Engineering 4 6%
Unspecified 3 4%
Other 9 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 August 2015.
All research outputs
#2,023,076
of 8,162,855 outputs
Outputs from Metabolomics
#145
of 538 outputs
Outputs of similar age
#52,849
of 197,616 outputs
Outputs of similar age from Metabolomics
#8
of 23 outputs
Altmetric has tracked 8,162,855 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 538 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 197,616 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.