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CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research

Overview of attention for article published in BMC Bioinformatics, December 2018
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
3 news outlets
twitter
1 X user

Citations

dimensions_citation
63 Dimensions

Readers on

mendeley
47 Mendeley
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Title
CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2508-4
Pubmed ID
Authors

Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson T. Collier, John Bauer, Fangfang Xia, Thomas Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia Cardona, Brian Van Essen, Matthew Baughman

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Bachelor 5 11%
Student > Master 4 9%
Student > Ph. D. Student 4 9%
Other 2 4%
Other 6 13%
Unknown 14 30%
Readers by discipline Count As %
Engineering 6 13%
Agricultural and Biological Sciences 5 11%
Medicine and Dentistry 5 11%
Computer Science 5 11%
Economics, Econometrics and Finance 2 4%
Other 8 17%
Unknown 16 34%
Attention Score in Context

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 15 October 2020.
All research outputs
#1,662,218
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#311
of 7,512 outputs
Outputs of similar age
#38,744
of 444,213 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 206 outputs
Altmetric has tracked 24,226,848 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 7,512 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 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 444,213 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 91% of its contemporaries.
We're also able to compare this research output to 206 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 94% of its contemporaries.