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Mendeley readers
Attention Score in Context
| Title |
Molecular Diagnosis of Neonatal Diabetes Mellitus Using Next-Generation Sequencing of the Whole Exome
|
|---|---|
| Published in |
PLOS ONE, October 2010
|
| DOI | 10.1371/journal.pone.0013630 |
| Pubmed ID | |
| Authors |
Amélie Bonnefond, Emmanuelle Durand, Olivier Sand, Franck De Graeve, Sophie Gallina, Kanetee Busiah, Stéphane Lobbens, Albane Simon, Christine Bellanné-Chantelot, Louis Létourneau, Raphael Scharfmann, Jérôme Delplanque, Robert Sladek, Michel Polak, Martine Vaxillaire, Philippe Froguel |
| Abstract |
Accurate molecular diagnosis of monogenic non-autoimmune neonatal diabetes mellitus (NDM) is critical for patient care, as patients carrying a mutation in KCNJ11 or ABCC8 can be treated by oral sulfonylurea drugs instead of insulin therapy. This diagnosis is currently based on Sanger sequencing of at least 42 PCR fragments from the KCNJ11, ABCC8, and INS genes. Here, we assessed the feasibility of using the next-generation whole exome sequencing (WES) for the NDM molecular diagnosis. |
Mendeley readers
The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Norway | 1 | <1% |
| Hong Kong | 1 | <1% |
| Brazil | 1 | <1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Mexico | 1 | <1% |
| Unknown | 154 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 41 | 25% |
| Student > Ph. D. Student | 33 | 20% |
| Student > Bachelor | 20 | 12% |
| Student > Master | 19 | 12% |
| Professor > Associate Professor | 10 | 6% |
| Other | 23 | 14% |
| Unknown | 15 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 54 | 34% |
| Medicine and Dentistry | 38 | 24% |
| Biochemistry, Genetics and Molecular Biology | 32 | 20% |
| Nursing and Health Professions | 5 | 3% |
| Computer Science | 3 | 2% |
| Other | 9 | 6% |
| Unknown | 20 | 12% |
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 09 May 2013.
All research outputs
#7,184,958
of 22,710,079 outputs
Outputs from PLOS ONE
#85,079
of 193,906 outputs
Outputs of similar age
#34,593
of 99,353 outputs
Outputs of similar age from PLOS ONE
#515
of 941 outputs
Altmetric has tracked 22,710,079 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 193,906 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has gotten more attention than average, scoring higher than 54% 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 99,353 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 941 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.