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Genomic approaches to diagnose rare bone disorders

Overview of attention for article published in BONE, July 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
6 X users
facebook
3 Facebook pages

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
32 Mendeley
citeulike
1 CiteULike
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Title
Genomic approaches to diagnose rare bone disorders
Published in
BONE, July 2016
DOI 10.1016/j.bone.2016.07.020
Pubmed ID
Authors

Félix Falardeau, Maria Vittoria Camurri, Philippe M. Campeau

Abstract

Skeletal dysplasias are Mendelian disorders with a prevalence of approximatively 1 in every 5000 newborns and can usually be diagnosed based on clinical and radiological findings. However, given that some diseases can be caused by several different genes, and that some genes can cause a variety of different phenotypes, achieving a molecular diagnosis can be challenging. We review here different approaches, from single gene sequencing to genomic approaches using next-generation sequencing, to reach a molecular diagnosis for skeletal dysplasias. We will further describe the overall advantages and limitations of first, second and third-generation sequencing, including single gene sequencing, whole-exome and genome sequencing (WES and WGS), multiple gene panel sequencing and single molecule sequencing. We also provide a brief overview of potential future applications of emerging technologies.

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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 34%
Student > Bachelor 5 16%
Student > Ph. D. Student 5 16%
Other 3 9%
Student > Postgraduate 3 9%
Other 4 13%
Unknown 1 3%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 28%
Medicine and Dentistry 9 28%
Agricultural and Biological Sciences 5 16%
Business, Management and Accounting 2 6%
Unspecified 1 3%
Other 1 3%
Unknown 5 16%
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 03 August 2016.
All research outputs
#8,262,445
of 25,374,917 outputs
Outputs from BONE
#1,198
of 4,328 outputs
Outputs of similar age
#132,108
of 380,100 outputs
Outputs of similar age from BONE
#16
of 67 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 66th percentile.
So far Altmetric has tracked 4,328 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 71% 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 380,100 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 64% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.