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multiGSEA: a GSEA-based pathway enrichment analysis for multi-omics data

Overview of attention for article published in BMC Bioinformatics, December 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
15 X users

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
105 Mendeley
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Title
multiGSEA: a GSEA-based pathway enrichment analysis for multi-omics data
Published in
BMC Bioinformatics, December 2020
DOI 10.1186/s12859-020-03910-x
Pubmed ID
Authors

Sebastian Canzler, Jörg Hackermüller

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 24%
Student > Ph. D. Student 21 20%
Other 9 9%
Student > Master 8 8%
Student > Bachelor 4 4%
Other 12 11%
Unknown 26 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 27%
Agricultural and Biological Sciences 14 13%
Computer Science 6 6%
Medicine and Dentistry 5 5%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 12 11%
Unknown 37 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 08 April 2022.
All research outputs
#2,471,635
of 25,837,817 outputs
Outputs from BMC Bioinformatics
#600
of 7,763 outputs
Outputs of similar age
#65,493
of 529,196 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 148 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 92% 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 529,196 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.