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Predict multi-type drug–drug interactions in cold start scenario

Overview of attention for article published in BMC Bioinformatics, February 2022
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  • Average Attention Score compared to outputs of the same age

Mentioned by

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4 X users

Citations

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10 Dimensions

Readers on

mendeley
9 Mendeley
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Title
Predict multi-type drug–drug interactions in cold start scenario
Published in
BMC Bioinformatics, February 2022
DOI 10.1186/s12859-022-04610-4
Pubmed ID
Authors

Zun Liu, Xing-Nan Wang, Hui Yu, Jian-Yu Shi, Wen-Min Dong

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Professor 1 11%
Student > Bachelor 1 11%
Unknown 5 56%
Readers by discipline Count As %
Computer Science 3 33%
Social Sciences 1 11%
Unknown 5 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 February 2022.
All research outputs
#14,717,488
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#4,823
of 7,418 outputs
Outputs of similar age
#217,918
of 440,508 outputs
Outputs of similar age from BMC Bioinformatics
#96
of 133 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 440,508 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.