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A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life

Overview of attention for article published in Bioinformatics, December 2016
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  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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Article details
Title
A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
Published in
Bioinformatics, December 2016
DOI 10.1093/bioinformatics/btw728
Pubmed ID
Authors
Abstract

The aim of this study is to assess the performance of RNA-RNA interaction prediction tools for all domains of life. Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 1%
Japan 1 1%
Denmark 1 1%
Unknown 93 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 18 19%
Student > Master 17 18%
Researcher 16 17%
Student > Bachelor 15 16%
Professor > Associate Professor 3 3%
Other 8 8%
Unknown 19 20%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 27%
Agricultural and Biological Sciences 24 25%
Computer Science 10 10%
Medicine and Dentistry 4 4%
Engineering 4 4%
Other 7 7%
Unknown 21 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 May 2017.
All research outputs
#6,178,817
of 23,043,346 outputs
Outputs from Bioinformatics
#1,791
of 4,106 outputs
Outputs of similar age
#115,109
of 422,215 outputs
Outputs of similar age from Bioinformatics
#54
of 151 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 4,106 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has gotten more attention than average, scoring higher than 56% 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 422,215 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 151 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 64% of its contemporaries.