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Quadratic variance models for adaptively preprocessing SELDI-TOF mass spectrometry data

Overview of attention for article published in BMC Bioinformatics, October 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
10 Mendeley
citeulike
1 CiteULike
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Title
Quadratic variance models for adaptively preprocessing SELDI-TOF mass spectrometry data
Published in
BMC Bioinformatics, October 2010
DOI 10.1186/1471-2105-11-512
Pubmed ID
Authors

Vincent A Emanuele, Brian M Gurbaxani

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 40%
Researcher 2 20%
Lecturer > Senior Lecturer 1 10%
Student > Master 1 10%
Unknown 2 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Veterinary Science and Veterinary Medicine 1 10%
Mathematics 1 10%
Computer Science 1 10%
Physics and Astronomy 1 10%
Other 2 20%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 17 September 2020.
All research outputs
#5,756,990
of 22,862,742 outputs
Outputs from BMC Bioinformatics
#2,144
of 7,294 outputs
Outputs of similar age
#28,305
of 99,113 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 52 outputs
Altmetric has tracked 22,862,742 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,294 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 70% 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 99,113 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 70% of its contemporaries.
We're also able to compare this research output to 52 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 69% of its contemporaries.