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mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning

Overview of attention for article published in Frontiers in Genetics, January 2019
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2 X users

Citations

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Readers on

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85 Mendeley
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Title
mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning
Published in
Frontiers in Genetics, January 2019
DOI 10.3389/fgene.2018.00714
Pubmed ID
Authors

Zhenzhen Zou, Shuye Tian, Xin Gao, Yu Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 13%
Student > Ph. D. Student 10 12%
Researcher 9 11%
Student > Doctoral Student 7 8%
Student > Bachelor 4 5%
Other 12 14%
Unknown 32 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 14%
Computer Science 11 13%
Agricultural and Biological Sciences 8 9%
Chemistry 6 7%
Chemical Engineering 3 4%
Other 6 7%
Unknown 39 46%
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 26 January 2019.
All research outputs
#18,664,348
of 23,124,001 outputs
Outputs from Frontiers in Genetics
#7,190
of 12,167 outputs
Outputs of similar age
#324,490
of 437,601 outputs
Outputs of similar age from Frontiers in Genetics
#226
of 305 outputs
Altmetric has tracked 23,124,001 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,167 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 27th percentile – i.e., 27% 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 437,601 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 305 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.