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RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure

Overview of attention for article published in BMC Bioinformatics, March 2008
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
2 X users
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
36 Mendeley
citeulike
1 CiteULike
connotea
1 Connotea
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Title
RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure
Published in
BMC Bioinformatics, March 2008
DOI 10.1186/1471-2105-9-176
Pubmed ID
Authors

Qi Liu, Yu Yang, Chun Chen, Jiajun Bu, Yin Zhang, Xiuzi Ye

Abstract

With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression.

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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 6%
Indonesia 2 6%
Germany 1 3%
France 1 3%
Finland 1 3%
China 1 3%
Unknown 28 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 25%
Student > Bachelor 6 17%
Student > Postgraduate 5 14%
Student > Master 4 11%
Other 3 8%
Other 8 22%
Unknown 1 3%
Readers by discipline Count As %
Computer Science 11 31%
Agricultural and Biological Sciences 7 19%
Social Sciences 6 17%
Biochemistry, Genetics and Molecular Biology 3 8%
Chemistry 2 6%
Other 6 17%
Unknown 1 3%
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 04 January 2021.
All research outputs
#5,879,023
of 22,785,242 outputs
Outputs from BMC Bioinformatics
#2,166
of 7,279 outputs
Outputs of similar age
#24,356
of 82,176 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 43 outputs
Altmetric has tracked 22,785,242 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 7,279 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 69% 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 82,176 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 69% of its contemporaries.
We're also able to compare this research output to 43 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 69% of its contemporaries.