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Prediction of drug-disease associations based on ensemble meta paths and singular value decomposition

Overview of attention for article published in BMC Bioinformatics, March 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
39 Mendeley
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Title
Prediction of drug-disease associations based on ensemble meta paths and singular value decomposition
Published in
BMC Bioinformatics, March 2019
DOI 10.1186/s12859-019-2644-5
Pubmed ID
Authors

Guangsheng Wu, Juan Liu, Xiang Yue

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Student > Bachelor 4 10%
Student > Master 3 8%
Student > Doctoral Student 2 5%
Other 2 5%
Other 4 10%
Unknown 15 38%
Readers by discipline Count As %
Computer Science 11 28%
Biochemistry, Genetics and Molecular Biology 4 10%
Medicine and Dentistry 2 5%
Engineering 2 5%
Business, Management and Accounting 1 3%
Other 4 10%
Unknown 15 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 19 July 2023.
All research outputs
#5,556,651
of 25,755,403 outputs
Outputs from BMC Bioinformatics
#1,960
of 7,741 outputs
Outputs of similar age
#107,091
of 365,232 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 162 outputs
Altmetric has tracked 25,755,403 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,741 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 gotten more attention than average, scoring higher than 73% 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 365,232 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 162 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 72% of its contemporaries.