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Cnidaria: fast, reference-free clustering of raw and assembled genome and transcriptome NGS data

Overview of attention for article published in BMC Bioinformatics, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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16 X users

Citations

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12 Dimensions

Readers on

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32 Mendeley
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Title
Cnidaria: fast, reference-free clustering of raw and assembled genome and transcriptome NGS data
Published in
BMC Bioinformatics, November 2015
DOI 10.1186/s12859-015-0806-7
Pubmed ID
Authors

Saulo Alves Aflitos, Edouard Severing, Gabino Sanchez-Perez, Sander Peters, Hans de Jong, Dick de Ridder

Abstract

Identification of biological specimens is a requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but generally do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances. We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on genome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100 % identification accuracy at supra-species level and 78 % accuracy at the species level. CNIDARIA allows for fast, resource-efficient comparison and identification of both raw and assembled genome and transcriptome data. This can help answer both fundamental (e.g. in phylogeny, ecological diversity analysis) and practical questions (e.g. sequencing quality control, primer design).

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Netherlands 1 3%
Brazil 1 3%
Unknown 29 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Ph. D. Student 7 22%
Other 4 13%
Professor 2 6%
Unspecified 1 3%
Other 3 9%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 44%
Computer Science 4 13%
Biochemistry, Genetics and Molecular Biology 4 13%
Unspecified 1 3%
Environmental Science 1 3%
Other 2 6%
Unknown 6 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 12 April 2022.
All research outputs
#3,043,285
of 23,523,017 outputs
Outputs from BMC Bioinformatics
#1,042
of 7,406 outputs
Outputs of similar age
#44,273
of 286,639 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 155 outputs
Altmetric has tracked 23,523,017 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,406 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 done well, scoring higher than 85% 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 286,639 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 155 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 90% of its contemporaries.