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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic variants associated with neurodegenerative Alzheimer disease in natural models
|
|---|---|
| Published in |
Biological Research, February 2016
|
| DOI | 10.1186/s40659-016-0072-9 |
| Pubmed ID | |
| Authors |
Claudia Salazar, Gonzalo Valdivia, Álvaro O. Ardiles, John Ewer, Adrián G. Palacios |
| Abstract |
The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 1% |
| Italy | 1 | 1% |
| France | 1 | 1% |
| Unknown | 68 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 14 | 20% |
| Researcher | 11 | 15% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Master | 7 | 10% |
| Student > Postgraduate | 4 | 6% |
| Other | 8 | 11% |
| Unknown | 19 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 18% |
| Neuroscience | 9 | 13% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Medicine and Dentistry | 8 | 11% |
| Psychology | 4 | 6% |
| Other | 6 | 8% |
| Unknown | 23 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 17 March 2016.
All research outputs
#3,083,565
of 25,394,764 outputs
Outputs from Biological Research
#24
of 642 outputs
Outputs of similar age
#46,377
of 312,388 outputs
Outputs of similar age from Biological Research
#1
of 18 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 642 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 96% 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 312,388 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.