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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)

Mentioned by

twitter
25 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
45 Mendeley
citeulike
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.

Twitter Demographics

The data shown below were collected from the profiles of 25 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 4 9%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 53%
Computer Science 6 13%
Biochemistry, Genetics and Molecular Biology 4 9%
Mathematics 2 4%
Business, Management and Accounting 1 2%
Other 1 2%
Unknown 7 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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
#1,774,361
of 21,344,814 outputs
Outputs from BMC Genomics
#499
of 10,275 outputs
Outputs of similar age
#14,238
of 169,922 outputs
Outputs of similar age from BMC Genomics
#1
of 4 outputs
Altmetric has tracked 21,344,814 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,275 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% 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 169,922 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them