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Prediction of lncRNA-disease association based on a Laplace normalized random walk with restart algorithm on heterogeneous networks

Overview of attention for article published in BMC Bioinformatics, January 2022
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1 X user

Citations

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17 Dimensions

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9 Mendeley
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Title
Prediction of lncRNA-disease association based on a Laplace normalized random walk with restart algorithm on heterogeneous networks
Published in
BMC Bioinformatics, January 2022
DOI 10.1186/s12859-021-04538-1
Pubmed ID
Authors

Liugen Wang, Min Shang, Qi Dai, Ping-an He

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 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%
Researcher 1 11%
Other 1 11%
Student > Master 1 11%
Unknown 4 44%
Readers by discipline Count As %
Computer Science 4 44%
Biochemistry, Genetics and Molecular Biology 2 22%
Unknown 3 33%
Attention Score in Context

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 05 January 2022.
All research outputs
#20,284,384
of 22,818,766 outputs
Outputs from BMC Bioinformatics
#6,855
of 7,284 outputs
Outputs of similar age
#409,591
of 499,544 outputs
Outputs of similar age from BMC Bioinformatics
#139
of 141 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,284 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 1st percentile – i.e., 1% 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 499,544 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.