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GNE: a deep learning framework for gene network inference by aggregating biological information

Overview of attention for article published in BMC Systems Biology, April 2019
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Readers on

mendeley
54 Mendeley
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Title
GNE: a deep learning framework for gene network inference by aggregating biological information
Published in
BMC Systems Biology, April 2019
DOI 10.1186/s12918-019-0694-y
Pubmed ID
Authors

Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne R. Haake

Twitter Demographics

The data shown below were collected from the profiles of 5 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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 30%
Researcher 9 17%
Student > Master 9 17%
Other 4 7%
Student > Bachelor 3 6%
Other 4 7%
Unknown 9 17%
Readers by discipline Count As %
Computer Science 17 31%
Biochemistry, Genetics and Molecular Biology 13 24%
Engineering 6 11%
Agricultural and Biological Sciences 3 6%
Medicine and Dentistry 2 4%
Other 2 4%
Unknown 11 20%

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 19 April 2020.
All research outputs
#9,063,151
of 15,465,536 outputs
Outputs from BMC Systems Biology
#490
of 1,106 outputs
Outputs of similar age
#142,111
of 270,506 outputs
Outputs of similar age from BMC Systems Biology
#5
of 12 outputs
Altmetric has tracked 15,465,536 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,106 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 50% 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 270,506 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 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 50% of its contemporaries.