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Genome reassembly with high-throughput sequencing data

Overview of attention for article published in BMC Genomics, January 2013
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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24 X users

Citations

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3 Dimensions

Readers on

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45 Mendeley
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1 CiteULike
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Title
Genome reassembly with high-throughput sequencing data
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-s1-s8
Pubmed ID
Authors

Nathaniel Parrish, Benjamin Sudakov, Eleazar Eskin

Abstract

Recent studies in genomics have highlighted the significance of structural variation in determining individual variation. Current methods for identifying structural variation, however, are predominantly focused on either assembling whole genomes from scratch, or identifying the relatively small changes between a genome and a reference sequence. While significant progress has been made in recent years on both de novo assembly and resequencing (read mapping) methods, few attempts have been made to bridge the gap between them.

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 7%
France 2 4%
Norway 1 2%
Italy 1 2%
Hungary 1 2%
Finland 1 2%
Sweden 1 2%
Japan 1 2%
India 1 2%
Other 0 0%
Unknown 33 73%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 40%
Student > Ph. D. Student 9 20%
Student > Bachelor 5 11%
Student > Postgraduate 3 7%
Student > Doctoral Student 2 4%
Other 3 7%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 56%
Computer Science 6 13%
Biochemistry, Genetics and Molecular Biology 3 7%
Mathematics 2 4%
Business, Management and Accounting 1 2%
Other 1 2%
Unknown 7 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 April 2013.
All research outputs
#2,309,459
of 24,562,945 outputs
Outputs from BMC Genomics
#622
of 11,010 outputs
Outputs of similar age
#23,098
of 288,503 outputs
Outputs of similar age from BMC Genomics
#32
of 365 outputs
Altmetric has tracked 24,562,945 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,010 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 94% 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 288,503 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 91% of its contemporaries.
We're also able to compare this research output to 365 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 91% of its contemporaries.