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Application of transfer learning for cancer drug sensitivity prediction

Overview of attention for article published in BMC Bioinformatics, December 2018
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Application of transfer learning for cancer drug sensitivity prediction
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2465-y
Pubmed ID
Authors

Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal

Twitter Demographics

The data shown below were collected from the profiles of 2 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Researcher 5 15%
Student > Bachelor 2 6%
Student > Doctoral Student 2 6%
Lecturer > Senior Lecturer 1 3%
Other 5 15%
Unknown 11 32%
Readers by discipline Count As %
Computer Science 7 21%
Biochemistry, Genetics and Molecular Biology 6 18%
Engineering 3 9%
Mathematics 3 9%
Agricultural and Biological Sciences 2 6%
Other 2 6%
Unknown 11 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 31 December 2018.
All research outputs
#12,361,236
of 18,804,592 outputs
Outputs from BMC Bioinformatics
#4,623
of 6,433 outputs
Outputs of similar age
#243,032
of 400,772 outputs
Outputs of similar age from BMC Bioinformatics
#282
of 415 outputs
Altmetric has tracked 18,804,592 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,433 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 400,772 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 415 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.