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DeepGRP: engineering a software tool for predicting genomic repetitive elements using Recurrent Neural Networks with attention

Overview of attention for article published in Algorithms for Molecular Biology, August 2021
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
39 Mendeley
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Title
DeepGRP: engineering a software tool for predicting genomic repetitive elements using Recurrent Neural Networks with attention
Published in
Algorithms for Molecular Biology, August 2021
DOI 10.1186/s13015-021-00199-0
Authors

Fabian Hausmann, Stefan Kurtz

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 8%
Professor 1 3%
Student > Master 1 3%
Unknown 34 87%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 3%
Business, Management and Accounting 1 3%
Computer Science 1 3%
Engineering 1 3%
Unknown 35 90%

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 30 November 2021.
All research outputs
#17,299,907
of 19,541,023 outputs
Outputs from Algorithms for Molecular Biology
#203
of 245 outputs
Outputs of similar age
#266,174
of 334,590 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 1 outputs
Altmetric has tracked 19,541,023 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 245 research outputs from this source. They receive a mean Attention Score of 3.1. 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 334,590 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them