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An auditory display tool for DNA sequence analysis

Overview of attention for article published in BMC Bioinformatics, April 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#13 of 7,606)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
5 news outlets
blogs
4 blogs
twitter
48 X users
facebook
2 Facebook pages
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
64 Mendeley
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Title
An auditory display tool for DNA sequence analysis
Published in
BMC Bioinformatics, April 2017
DOI 10.1186/s12859-017-1632-x
Pubmed ID
Authors

Mark D. Temple

Abstract

DNA Sonification refers to the use of an auditory display to convey the information content of DNA sequence data. Six sonification algorithms are presented that each produce an auditory display. These algorithms are logically designed from the simple through to the more complex. Three of these parse individual nucleotides, nucleotide pairs or codons into musical notes to give rise to 4, 16 or 64 notes, respectively. Codons may also be parsed degenerately into 20 notes with respect to the genetic code. Lastly nucleotide pairs can be parsed as two separate frames or codons can be parsed as three reading frames giving rise to multiple streams of audio. The most informative sonification algorithm reads the DNA sequence as codons in three reading frames to produce three concurrent streams of audio in an auditory display. This approach is advantageous since start and stop codons in either frame have a direct affect to start or stop the audio in that frame, leaving the other frames unaffected. Using these methods, DNA sequences such as open reading frames or repetitive DNA sequences can be distinguished from one another. These sonification tools are available through a webpage interface in which an input DNA sequence can be processed in real time to produce an auditory display playable directly within the browser. The potential of this approach as an analytical tool is discussed with reference to auditory displays derived from test sequences including simple nucleotide sequences, repetitive DNA sequences and coding or non-coding genes. This study presents a proof-of-concept that some properties of a DNA sequence can be identified through sonification alone and argues for their inclusion within the toolkit of DNA sequence browsers as an adjunct to existing visual and analytical tools.

X Demographics

X Demographics

The data shown below were collected from the profiles of 48 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 63 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 19%
Student > Master 9 14%
Student > Bachelor 7 11%
Professor 6 9%
Other 6 9%
Other 13 20%
Unknown 11 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 22%
Agricultural and Biological Sciences 12 19%
Computer Science 8 13%
Engineering 5 8%
Philosophy 2 3%
Other 9 14%
Unknown 14 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 100. 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 26 April 2023.
All research outputs
#409,214
of 24,903,209 outputs
Outputs from BMC Bioinformatics
#13
of 7,606 outputs
Outputs of similar age
#8,597
of 315,176 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 125 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,606 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 99% 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 315,176 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 125 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.