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A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters

Overview of attention for article published in BMC Bioinformatics, March 2012
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
32 Mendeley
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Title
A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters
Published in
BMC Bioinformatics, March 2012
DOI 10.1186/1471-2105-13-s3-s15
Pubmed ID
Authors

Youngik Yang, Kenneth Nephew, Sun Kim

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 38%
Student > Ph. D. Student 5 16%
Professor 2 6%
Student > Doctoral Student 2 6%
Student > Postgraduate 2 6%
Other 5 16%
Unknown 4 13%
Readers by discipline Count As %
Computer Science 8 25%
Agricultural and Biological Sciences 7 22%
Biochemistry, Genetics and Molecular Biology 4 13%
Neuroscience 2 6%
Nursing and Health Professions 1 3%
Other 4 13%
Unknown 6 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 April 2019.
All research outputs
#7,588,614
of 23,138,859 outputs
Outputs from BMC Bioinformatics
#3,054
of 7,339 outputs
Outputs of similar age
#53,237
of 161,586 outputs
Outputs of similar age from BMC Bioinformatics
#24
of 70 outputs
Altmetric has tracked 23,138,859 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,339 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 50% 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 161,586 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 70 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 54% of its contemporaries.