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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Pathogenicity of new BEST1 variants identified in Italian patients with best vitelliform macular dystrophy assessed by computational structural biology
|
|---|---|
| Published in |
Journal of Translational Medicine, October 2019
|
| DOI | 10.1186/s12967-019-2080-3 |
| Pubmed ID | |
| Authors |
Vladimir Frecer, Giancarlo Iarossi, Anna Paola Salvetti, Paolo Enrico Maltese, Giulia Delledonne, Marta Oldani, Giovanni Staurenghi, Benedetto Falsini, Angelo Maria Minnella, Lucia Ziccardi, Adriano Magli, Leonardo Colombo, Fabiana D’Esposito, Jan Miertus, Francesco Viola, Marcella Attanasio, Emilia Maggio, Matteo Bertelli |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 14% |
| Student > Bachelor | 3 | 14% |
| Student > Ph. D. Student | 2 | 9% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 8 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 23% |
| Medicine and Dentistry | 4 | 18% |
| Business, Management and Accounting | 1 | 5% |
| Computer Science | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 8 | 36% |
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 02 October 2019.
All research outputs
#20,582,908
of 23,166,665 outputs
Outputs from Journal of Translational Medicine
#3,366
of 4,070 outputs
Outputs of similar age
#297,444
of 349,851 outputs
Outputs of similar age from Journal of Translational Medicine
#48
of 61 outputs
Altmetric has tracked 23,166,665 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,070 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 1st percentile – i.e., 1% 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 349,851 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 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.