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A novel bi-directional heterogeneous network selection method for disease and microbial association prediction

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

Mentioned by

twitter
4 X users

Citations

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1 Dimensions

Readers on

mendeley
5 Mendeley
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Title
A novel bi-directional heterogeneous network selection method for disease and microbial association prediction
Published in
BMC Bioinformatics, November 2022
DOI 10.1186/s12859-022-04961-y
Pubmed ID
Authors

Jian Guan, Zhao Gong Zhang, Yong Liu, Meng Wang

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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Unknown 4 80%
Readers by discipline Count As %
Computer Science 1 20%
Unknown 4 80%
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 16 November 2022.
All research outputs
#15,673,350
of 24,826,104 outputs
Outputs from BMC Bioinformatics
#4,930
of 7,594 outputs
Outputs of similar age
#209,637
of 426,676 outputs
Outputs of similar age from BMC Bioinformatics
#104
of 161 outputs
Altmetric has tracked 24,826,104 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,594 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 31st percentile – i.e., 31% 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 426,676 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 161 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.