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CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers

Overview of attention for article published in BMC Genomics, March 2015
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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 (#45 of 11,367)
  • 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
3 blogs
policy
1 policy source
twitter
18 X users
patent
4 patents
peer_reviews
1 peer review site
facebook
1 Facebook page
wikipedia
6 Wikipedia pages

Citations

dimensions_citation
532 Dimensions

Readers on

mendeley
532 Mendeley
citeulike
5 CiteULike
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Title
CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers
Published in
BMC Genomics, March 2015
DOI 10.1186/s12864-015-1419-2
Pubmed ID
Authors

Rachid Ounit, Steve Wanamaker, Timothy J Close, Stefano Lonardi

Abstract

The problem of supervised DNA sequence classification arises in several fields of computational molecular biology. Although this problem has been extensively studied, it is still computationally challenging due to size of the datasets that modern sequencing technologies can produce. We introduce CLARK a novel approach to classify metagenomic reads at the species or genus level with high accuracy and high speed. Extensive experimental results on various metagenomic samples show that the classification accuracy of CLARK is better or comparable to the best state-of-the-art tools and it is significantly faster than any of its competitors. In its fastest single-threaded mode CLARK classifies, with high accuracy, about 32 million metagenomic short reads per minute. CLARK can also classify BAC clones or transcripts to chromosome arms and centromeric regions. CLARK is a versatile, fast and accurate sequence classification method, especially useful for metagenomics and genomics applications. It is freely available at http://clark.cs.ucr.edu/ .

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 532 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
Canada 3 <1%
Brazil 3 <1%
France 2 <1%
Estonia 2 <1%
Germany 2 <1%
Sweden 2 <1%
United Kingdom 2 <1%
Norway 1 <1%
Other 4 <1%
Unknown 502 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 117 22%
Researcher 100 19%
Student > Master 76 14%
Student > Bachelor 53 10%
Student > Doctoral Student 30 6%
Other 71 13%
Unknown 85 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 162 30%
Biochemistry, Genetics and Molecular Biology 119 22%
Computer Science 73 14%
Engineering 16 3%
Environmental Science 14 3%
Other 48 9%
Unknown 100 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 87. 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 17 May 2022.
All research outputs
#498,624
of 25,837,817 outputs
Outputs from BMC Genomics
#45
of 11,367 outputs
Outputs of similar age
#5,753
of 281,181 outputs
Outputs of similar age from BMC Genomics
#1
of 282 outputs
Altmetric has tracked 25,837,817 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 11,367 research outputs from this source. They receive a mean Attention Score of 4.9. 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 281,181 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 282 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.