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Resolving complex structural genomic rearrangements using a randomized approach

Overview of attention for article published in Genome Biology, June 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

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6 X users

Citations

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40 Dimensions

Readers on

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88 Mendeley
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2 CiteULike
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Title
Resolving complex structural genomic rearrangements using a randomized approach
Published in
Genome Biology, June 2016
DOI 10.1186/s13059-016-0993-1
Pubmed ID
Authors

Xuefang Zhao, Sarah B. Emery, Bridget Myers, Jeffrey M. Kidd, Ryan E. Mills

Abstract

Complex chromosomal rearrangements are structural genomic alterations involving multiple instances of deletions, duplications, inversions, or translocations that co-occur either on the same chromosome or represent different overlapping events on homologous chromosomes. We present SVelter, an algorithm that identifies regions of the genome suspected to harbor a complex event and then resolves the structure by iteratively rearranging the local genome structure, in a randomized fashion, with each structure scored against characteristics of the observed sequencing data. SVelter is able to accurately reconstruct complex chromosomal rearrangements when compared to well-characterized genomes that have been deeply sequenced with both short and long reads.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Korea, Republic of 1 1%
Netherlands 1 1%
Brazil 1 1%
Unknown 83 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 26%
Researcher 18 20%
Student > Bachelor 9 10%
Student > Master 9 10%
Student > Doctoral Student 5 6%
Other 9 10%
Unknown 15 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 28%
Agricultural and Biological Sciences 25 28%
Computer Science 10 11%
Medicine and Dentistry 5 6%
Mathematics 2 2%
Other 6 7%
Unknown 15 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 June 2016.
All research outputs
#7,714,565
of 25,374,917 outputs
Outputs from Genome Biology
#3,359
of 4,467 outputs
Outputs of similar age
#116,568
of 360,136 outputs
Outputs of similar age from Genome Biology
#67
of 83 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 360,136 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.