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Comparison of mapping algorithms used in high-throughput sequencing: application to Ion Torrent data

Overview of attention for article published in BMC Genomics, April 2014
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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29 X users
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5 patents
googleplus
1 Google+ user

Citations

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83 Dimensions

Readers on

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225 Mendeley
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Title
Comparison of mapping algorithms used in high-throughput sequencing: application to Ion Torrent data
Published in
BMC Genomics, April 2014
DOI 10.1186/1471-2164-15-264
Pubmed ID
Authors

Ségolène Caboche, Christophe Audebert, Yves Lemoine, David Hot

Abstract

The rapid evolution in high-throughput sequencing (HTS) technologies has opened up new perspectives in several research fields and led to the production of large volumes of sequence data. A fundamental step in HTS data analysis is the mapping of reads onto reference sequences. Choosing a suitable mapper for a given technology and a given application is a subtle task because of the difficulty of evaluating mapping algorithms.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 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 225 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
Netherlands 3 1%
Brazil 3 1%
France 2 <1%
Italy 2 <1%
Switzerland 1 <1%
Finland 1 <1%
Canada 1 <1%
Chile 1 <1%
Other 8 4%
Unknown 199 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 66 29%
Student > Ph. D. Student 52 23%
Student > Master 28 12%
Student > Bachelor 17 8%
Other 10 4%
Other 26 12%
Unknown 26 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 95 42%
Biochemistry, Genetics and Molecular Biology 45 20%
Computer Science 25 11%
Medicine and Dentistry 6 3%
Engineering 4 2%
Other 16 7%
Unknown 34 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 07 November 2023.
All research outputs
#1,698,086
of 25,374,917 outputs
Outputs from BMC Genomics
#340
of 11,244 outputs
Outputs of similar age
#16,806
of 239,354 outputs
Outputs of similar age from BMC Genomics
#5
of 227 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 96% 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 239,354 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 92% of its contemporaries.
We're also able to compare this research output to 227 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 97% of its contemporaries.