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Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

Overview of attention for article published in BMC Bioinformatics, November 2010
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
twitter
4 tweeters
patent
5 patents

Citations

dimensions_citation
1345 Dimensions

Readers on

mendeley
1158 Mendeley
citeulike
7 CiteULike
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Title
Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
Published in
BMC Bioinformatics, November 2010
DOI 10.1186/1471-2105-11-587
Pubmed ID
Authors

Pan Du, Xiao Zhang, Chiang-Ching Huang, Nadereh Jafari, Warren A Kibbe, Lifang Hou, Simon M Lin

Twitter Demographics

The data shown below were collected from the profiles of 4 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 1,158 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 18 2%
United Kingdom 5 <1%
Spain 4 <1%
Brazil 4 <1%
Germany 3 <1%
Canada 3 <1%
Sweden 3 <1%
Switzerland 2 <1%
Japan 2 <1%
Other 18 2%
Unknown 1096 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 312 27%
Researcher 232 20%
Student > Master 138 12%
Student > Bachelor 103 9%
Student > Doctoral Student 73 6%
Other 157 14%
Unknown 143 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 346 30%
Biochemistry, Genetics and Molecular Biology 257 22%
Medicine and Dentistry 120 10%
Computer Science 69 6%
Mathematics 37 3%
Other 138 12%
Unknown 191 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 March 2022.
All research outputs
#1,446,242
of 21,963,432 outputs
Outputs from BMC Bioinformatics
#295
of 7,072 outputs
Outputs of similar age
#29,962
of 406,009 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 513 outputs
Altmetric has tracked 21,963,432 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,072 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 done particularly well, scoring higher than 95% 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 406,009 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 513 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 96% of its contemporaries.