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FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network

Overview of attention for article published in Frontiers in Genetics, November 2020
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1 X user

Citations

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20 Mendeley
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Title
FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network
Published in
Frontiers in Genetics, November 2020
DOI 10.3389/fgene.2020.564839
Pubmed ID
Authors

Hong Gu, Xiaolu Xu, Pan Qin, Jia Wang

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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.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 25%
Student > Bachelor 3 15%
Student > Postgraduate 2 10%
Student > Doctoral Student 1 5%
Researcher 1 5%
Other 1 5%
Unknown 7 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 15%
Computer Science 3 15%
Agricultural and Biological Sciences 2 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Engineering 1 5%
Other 1 5%
Unknown 9 45%
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 16 December 2020.
All research outputs
#20,675,093
of 23,269,984 outputs
Outputs from Frontiers in Genetics
#8,885
of 12,291 outputs
Outputs of similar age
#355,346
of 415,925 outputs
Outputs of similar age from Frontiers in Genetics
#327
of 462 outputs
Altmetric has tracked 23,269,984 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 12,291 research outputs from this source. They receive a mean Attention Score of 3.7. 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 415,925 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 462 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.