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A model-based circular binary segmentation algorithm for the analysis of array CGH data

Overview of attention for article published in BMC Research Notes, October 2011
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
2 patents

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
12 Mendeley
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Title
A model-based circular binary segmentation algorithm for the analysis of array CGH data
Published in
BMC Research Notes, October 2011
DOI 10.1186/1756-0500-4-394
Pubmed ID
Authors

Fang-Han Hsu, Hung-I H Chen, Mong-Hsun Tsai, Liang-Chuan Lai, Chi-Cheng Huang, Shih-Hsin Tu, Eric Y Chuang, Yidong Chen

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 25%
Professor > Associate Professor 2 17%
Student > Master 2 17%
Student > Ph. D. Student 1 8%
Student > Doctoral Student 1 8%
Other 1 8%
Unknown 2 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 25%
Agricultural and Biological Sciences 3 25%
Computer Science 1 8%
Medicine and Dentistry 1 8%
Engineering 1 8%
Other 0 0%
Unknown 3 25%
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 26 February 2015.
All research outputs
#7,551,483
of 23,036,991 outputs
Outputs from BMC Research Notes
#1,249
of 4,283 outputs
Outputs of similar age
#46,534
of 136,935 outputs
Outputs of similar age from BMC Research Notes
#25
of 63 outputs
Altmetric has tracked 23,036,991 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 4,283 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 gotten more attention than average, scoring higher than 65% 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 136,935 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.