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Capturing alternative secondary structures of RNA by decomposition of base-pairing probabilities

Overview of attention for article published in BMC Bioinformatics, February 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

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4 tweeters

Citations

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6 Dimensions

Readers on

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25 Mendeley
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Title
Capturing alternative secondary structures of RNA by decomposition of base-pairing probabilities
Published in
BMC Bioinformatics, February 2018
DOI 10.1186/s12859-018-2018-4
Pubmed ID
Authors

Taichi Hagio, Shun Sakuraba, Junichi Iwakiri, Ryota Mori, Kiyoshi Asai

Abstract

It is known that functional RNAs often switch their functions by forming different secondary structures. Popular tools for RNA secondary structures prediction, however, predict the single 'best' structures, and do not produce alternative structures. There are bioinformatics tools to predict suboptimal structures, but it is difficult to detect which alternative secondary structures are essential. We proposed a new computational method to detect essential alternative secondary structures from RNA sequences by decomposing the base-pairing probability matrix. The decomposition is calculated by a newly implemented software tool, RintW, which efficiently computes the base-pairing probability distributions over the Hamming distance from arbitrary reference secondary structures. The proposed approach has been demonstrated on ROSE element RNA thermometer sequence and Lysine RNA ribo-switch, showing that the proposed approach captures conformational changes in secondary structures. We have shown that alternative secondary structures are captured by decomposing base-paring probabilities over Hamming distance. Source code is available from http://www.ncRNA.org/RintW .

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 4 16%
Student > Ph. D. Student 4 16%
Professor 3 12%
Student > Master 3 12%
Other 3 12%
Other 5 20%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 7 28%
Biochemistry, Genetics and Molecular Biology 6 24%
Agricultural and Biological Sciences 5 20%
Medicine and Dentistry 2 8%
Physics and Astronomy 1 4%
Other 1 4%
Unknown 3 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 July 2018.
All research outputs
#11,518,831
of 20,513,123 outputs
Outputs from BMC Bioinformatics
#3,524
of 6,788 outputs
Outputs of similar age
#134,743
of 291,676 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 23 outputs
Altmetric has tracked 20,513,123 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,788 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 45th percentile – i.e., 45% 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 291,676 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 52% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.