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Next generation sequencing with copy number variant detection expands the phenotypic spectrum of HSD17B4-deficiency

Overview of attention for article published in BMC Medical Genomics, March 2014
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2 X users

Citations

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61 Mendeley
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Title
Next generation sequencing with copy number variant detection expands the phenotypic spectrum of HSD17B4-deficiency
Published in
BMC Medical Genomics, March 2014
DOI 10.1186/1471-2350-15-30
Pubmed ID
Authors

Daniel S Lieber, Steven G Hershman, Nancy G Slate, Sarah E Calvo, Katherine B Sims, Jeremy D Schmahmann, Vamsi K Mootha

Abstract

D-bifunctional protein deficiency, caused by recessive mutations in HSD17B4, is a severe, infantile-onset disorder of peroxisomal fatty acid oxidation. Few affected patients survive past two years of age. Compound heterozygous mutations in HSD17B4 have also been reported in two sisters diagnosed with Perrault syndrome (MIM # 233400), who presented in adolescence with ovarian dysgenesis, hearing loss, and ataxia.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 60 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 13%
Student > Ph. D. Student 7 11%
Student > Bachelor 7 11%
Student > Master 6 10%
Professor 5 8%
Other 15 25%
Unknown 13 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 20%
Medicine and Dentistry 11 18%
Agricultural and Biological Sciences 11 18%
Nursing and Health Professions 3 5%
Neuroscience 2 3%
Other 5 8%
Unknown 17 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 March 2014.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from BMC Medical Genomics
#1,102
of 2,444 outputs
Outputs of similar age
#129,050
of 235,895 outputs
Outputs of similar age from BMC Medical Genomics
#12
of 26 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,444 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 51% 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 235,895 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 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 50% of its contemporaries.