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Diagnosis of Noonan syndrome and related disorders using target next generation sequencing

Overview of attention for article published in BMC Medical Genomics, January 2014
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Title
Diagnosis of Noonan syndrome and related disorders using target next generation sequencing
Published in
BMC Medical Genomics, January 2014
DOI 10.1186/1471-2350-15-14
Pubmed ID
Authors

Francesca Romana Lepri, Rossana Scavelli, Maria Cristina Digilio, Maria Gnazzo, Simona Grotta, Maria Lisa Dentici, Elisa Pisaneschi, Pietro Sirleto, Rossella Capolino, Anwar Baban, Serena Russo, Tiziana Franchin, Adriano Angioni, Bruno Dallapiccola

Abstract

Noonan syndrome is an autosomal dominant developmental disorder with a high phenotypic variability, which shares clinical features with other rare conditions, including LEOPARD syndrome, cardiofaciocutaneous syndrome, Noonan-like syndrome with loose anagen hair, and Costello syndrome. This group of related disorders, so-called RASopathies, is caused by germline mutations in distinct genes encoding for components of the RAS-MAPK signalling pathway. Due to high number of genes associated with these disorders, standard diagnostic testing requires expensive and time consuming approaches using Sanger sequencing. In this study we show how targeted Next Generation Sequencing (NGS) technique can enable accurate, faster and cost-effective diagnosis of RASopathies.

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

Geographical breakdown

Country Count As %
Mexico 1 <1%
Colombia 1 <1%
South Africa 1 <1%
Unknown 101 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 13%
Researcher 13 13%
Student > Master 12 12%
Student > Bachelor 11 11%
Other 7 7%
Other 19 18%
Unknown 29 28%
Readers by discipline Count As %
Medicine and Dentistry 30 29%
Biochemistry, Genetics and Molecular Biology 19 18%
Agricultural and Biological Sciences 9 9%
Computer Science 4 4%
Neuroscience 2 2%
Other 9 9%
Unknown 31 30%
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 25 January 2014.
All research outputs
#20,656,820
of 25,374,917 outputs
Outputs from BMC Medical Genomics
#1,682
of 2,444 outputs
Outputs of similar age
#243,179
of 320,699 outputs
Outputs of similar age from BMC Medical Genomics
#24
of 30 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% 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 is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.