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Molecular diagnostics for congenital hearing loss including 15 deafness genes using a next generation sequencing platform

Overview of attention for article published in BMC Medical Genomics, May 2012
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Title
Molecular diagnostics for congenital hearing loss including 15 deafness genes using a next generation sequencing platform
Published in
BMC Medical Genomics, May 2012
DOI 10.1186/1755-8794-5-17
Pubmed ID
Authors

Sarah De Keulenaer, Jan Hellemans, Steve Lefever, Jean-Pierre Renard, Joachim De Schrijver, Hendrik Van de Voorde, Mohammad Amin Tabatabaiefar, Filip Van Nieuwerburgh, Daisy Flamez, Filip Pattyn, Bieke Scharlaken, Dieter Deforce, Sofie Bekaert, Wim Van Criekinge, Jo Vandesompele, Guy Van Camp, Paul Coucke

Abstract

Hereditary hearing loss (HL) can originate from mutations in one of many genes involved in the complex process of hearing. Identification of the genetic defects in patients is currently labor intensive and expensive. While screening with Sanger sequencing for GJB2 mutations is common, this is not the case for the other known deafness genes (> 60). Next generation sequencing technology (NGS) has the potential to be much more cost efficient. Published methods mainly use hybridization based target enrichment procedures that are time saving and efficient, but lead to loss in sensitivity. In this study we used a semi-automated PCR amplification and NGS in order to combine high sensitivity, speed and cost efficiency.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Belgium 1 1%
South Africa 1 1%
Brazil 1 1%
Unknown 74 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 15%
Student > Ph. D. Student 10 13%
Student > Master 9 12%
Student > Bachelor 8 10%
Other 7 9%
Other 23 29%
Unknown 9 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 29%
Biochemistry, Genetics and Molecular Biology 19 24%
Medicine and Dentistry 15 19%
Engineering 2 3%
Social Sciences 2 3%
Other 4 5%
Unknown 13 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 May 2012.
All research outputs
#15,243,549
of 22,665,794 outputs
Outputs from BMC Medical Genomics
#671
of 1,211 outputs
Outputs of similar age
#104,111
of 163,854 outputs
Outputs of similar age from BMC Medical Genomics
#12
of 19 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,211 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 35th percentile – i.e., 35% 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 163,854 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.