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Erratum to: Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction

Overview of attention for article published in BMC Bioinformatics, February 2017
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

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2 Dimensions

Readers on

mendeley
4 Mendeley
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Title
Erratum to: Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction
Published in
BMC Bioinformatics, February 2017
DOI 10.1186/s12859-017-1508-0
Pubmed ID
Authors

Yuri Bento Marques, Alcione de Paiva Oliveira, Ana Tereza Ribeiro Vasconcelos, Fabio Ribeiro Cerqueira

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 50%
Student > Bachelor 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Physics and Astronomy 1 25%
Unknown 1 25%
Attention Score in Context

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 03 April 2018.
All research outputs
#15,393,464
of 22,953,506 outputs
Outputs from BMC Bioinformatics
#5,386
of 7,308 outputs
Outputs of similar age
#196,440
of 309,434 outputs
Outputs of similar age from BMC Bioinformatics
#94
of 149 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,308 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 26th percentile – i.e., 26% 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 309,434 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.