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Alignment-free analysis of barcode sequences by means of compression-based methods

Overview of attention for article published in BMC Bioinformatics, April 2013
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

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1 X user
wikipedia
1 Wikipedia page

Citations

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16 Dimensions

Readers on

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32 Mendeley
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Title
Alignment-free analysis of barcode sequences by means of compression-based methods
Published in
BMC Bioinformatics, April 2013
DOI 10.1186/1471-2105-14-s7-s4
Pubmed ID
Authors

Massimo La Rosa, Antonino Fiannaca, Riccardo Rizzo, Alfonso Urso

Abstract

The key idea of DNA barcode initiative is to identify, for each group of species belonging to different kingdoms of life, a short DNA sequence that can act as a true taxon barcode. DNA barcode represents a valuable type of information that can be integrated with ecological, genetic, and morphological data in order to obtain a more consistent taxonomy. Recent studies have shown that, for the animal kingdom, the mitochondrial gene cytochrome c oxidase I (COI), about 650 bp long, can be used as a barcode sequence for identification and taxonomic purposes of animals. In the present work we aims at introducing the use of an alignment-free approach in order to make taxonomic analysis of barcode sequences. Our approach is based on the use of two compression-based versions of non-computable Universal Similarity Metric (USM) class of distances. Our purpose is to justify the employ of USM also for the analysis of short DNA barcode sequences, showing how USM is able to correctly extract taxonomic information among those kind of sequences.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 3%
Italy 1 3%
Unknown 30 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 38%
Student > Ph. D. Student 7 22%
Student > Bachelor 3 9%
Professor 2 6%
Student > Master 2 6%
Other 5 16%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 38%
Biochemistry, Genetics and Molecular Biology 9 28%
Computer Science 8 25%
Business, Management and Accounting 1 3%
Arts and Humanities 1 3%
Other 0 0%
Unknown 1 3%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 January 2014.
All research outputs
#6,925,375
of 22,707,247 outputs
Outputs from BMC Bioinformatics
#2,682
of 7,256 outputs
Outputs of similar age
#58,984
of 196,447 outputs
Outputs of similar age from BMC Bioinformatics
#47
of 120 outputs
Altmetric has tracked 22,707,247 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,256 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 61% 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 196,447 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 68% of its contemporaries.
We're also able to compare this research output to 120 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 55% of its contemporaries.