↓ Skip to main content

Multiple-kernel learning for genomic data mining and prediction

Overview of attention for article published in BMC Bioinformatics, August 2019
Altmetric Badge

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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
13 X users

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
67 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Multiple-kernel learning for genomic data mining and prediction
Published in
BMC Bioinformatics, August 2019
DOI 10.1186/s12859-019-2992-1
Pubmed ID
Authors

Christopher M. Wilson, Kaiqiao Li, Xiaoqing Yu, Pei-Fen Kuan, Xuefeng Wang

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 22%
Student > Master 10 15%
Researcher 6 9%
Student > Bachelor 4 6%
Other 4 6%
Other 10 15%
Unknown 18 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 24%
Computer Science 12 18%
Agricultural and Biological Sciences 7 10%
Mathematics 3 4%
Medicine and Dentistry 3 4%
Other 7 10%
Unknown 19 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 14 September 2021.
All research outputs
#1,782,946
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#401
of 7,387 outputs
Outputs of similar age
#38,894
of 342,602 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 108 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 94% 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 342,602 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 88% of its contemporaries.
We're also able to compare this research output to 108 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 92% of its contemporaries.