↓ Skip to main content

DNA Barcode Sequence Identification Incorporating Taxonomic Hierarchy and within Taxon Variability

Overview of attention for article published in PLOS ONE, August 2011
Altmetric Badge

About this Attention Score

  • 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 (64th percentile)

Mentioned by

twitter
2 X users
patent
1 patent
facebook
1 Facebook page

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
182 Mendeley
citeulike
4 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
DNA Barcode Sequence Identification Incorporating Taxonomic Hierarchy and within Taxon Variability
Published in
PLOS ONE, August 2011
DOI 10.1371/journal.pone.0020552
Pubmed ID
Authors

Damon P. Little

Abstract

For DNA barcoding to succeed as a scientific endeavor an accurate and expeditious query sequence identification method is needed. Although a global multiple-sequence alignment can be generated for some barcoding markers (e.g. COI, rbcL), not all barcoding markers are as structurally conserved (e.g. matK). Thus, algorithms that depend on global multiple-sequence alignments are not universally applicable. Some sequence identification methods that use local pairwise alignments (e.g. BLAST) are unable to accurately differentiate between highly similar sequences and are not designed to cope with hierarchic phylogenetic relationships or within taxon variability. Here, I present a novel alignment-free sequence identification algorithm--BRONX--that accounts for observed within taxon variability and hierarchic relationships among taxa. BRONX identifies short variable segments and corresponding invariant flanking regions in reference sequences. These flanking regions are used to score variable regions in the query sequence without the production of a global multiple-sequence alignment. By incorporating observed within taxon variability into the scoring procedure, misidentifications arising from shared alleles/haplotypes are minimized. An explicit treatment of more inclusive terminals allows for separate identifications to be made for each taxonomic level and/or for user-defined terminals. BRONX performs better than all other methods when there is imperfect overlap between query and reference sequences (e.g. mini-barcode queries against a full-length barcode database). BRONX consistently produced better identifications at the genus-level for all query types.

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

Geographical breakdown

Country Count As %
Germany 3 2%
United States 3 2%
India 2 1%
Australia 2 1%
Cuba 1 <1%
Italy 1 <1%
Netherlands 1 <1%
Sweden 1 <1%
France 1 <1%
Other 2 1%
Unknown 165 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 42 23%
Student > Ph. D. Student 40 22%
Student > Master 23 13%
Student > Bachelor 17 9%
Professor 10 5%
Other 35 19%
Unknown 15 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 117 64%
Biochemistry, Genetics and Molecular Biology 22 12%
Computer Science 7 4%
Environmental Science 6 3%
Medicine and Dentistry 3 2%
Other 9 5%
Unknown 18 10%
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 10 February 2022.
All research outputs
#6,514,655
of 23,090,520 outputs
Outputs from PLOS ONE
#79,282
of 196,982 outputs
Outputs of similar age
#31,873
of 107,422 outputs
Outputs of similar age from PLOS ONE
#802
of 2,379 outputs
Altmetric has tracked 23,090,520 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 196,982 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one has gotten more attention than average, scoring higher than 58% 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 107,422 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 2,379 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.