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Algorithm-driven Artifacts in median polish summarization of Microarray data

Overview of attention for article published in BMC Bioinformatics, January 2010
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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 (79th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
83 Mendeley
citeulike
4 CiteULike
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Title
Algorithm-driven Artifacts in median polish summarization of Microarray data
Published in
BMC Bioinformatics, January 2010
DOI 10.1186/1471-2105-11-553
Pubmed ID
Authors

Federico M Giorgi, Anthony M Bolger, Marc Lohse, Bjoern Usadel

Abstract

High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification.

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Canada 2 2%
Portugal 1 1%
France 1 1%
Switzerland 1 1%
Germany 1 1%
Belgium 1 1%
Denmark 1 1%
Russia 1 1%
Other 1 1%
Unknown 71 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 37%
Researcher 23 28%
Student > Master 9 11%
Professor > Associate Professor 3 4%
Other 3 4%
Other 10 12%
Unknown 4 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 48%
Computer Science 11 13%
Biochemistry, Genetics and Molecular Biology 10 12%
Medicine and Dentistry 6 7%
Arts and Humanities 1 1%
Other 6 7%
Unknown 9 11%

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 10 May 2011.
All research outputs
#2,691,868
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#1,081
of 4,576 outputs
Outputs of similar age
#21,506
of 103,521 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 37 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 76% 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 103,521 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 79% of its contemporaries.
We're also able to compare this research output to 37 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 56% of its contemporaries.