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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integration of Machine Learning Methods to Dissect Genetically Imputed Transcriptomic Profiles in Alzheimer’s Disease
|
|---|---|
| Published in |
Frontiers in Genetics, September 2019
|
| DOI | 10.3389/fgene.2019.00726 |
| Pubmed ID | |
| Authors |
Carlo Maj, Tiago Azevedo, Valentina Giansanti, Oleg Borisov, Giovanna Maria Dimitri, Simeon Spasov, Alzheimer’s Disease Neuroimaging Initiative, Pietro Lió, Ivan Merelli |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 91 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 19% |
| Student > Master | 15 | 16% |
| Researcher | 10 | 11% |
| Unspecified | 4 | 4% |
| Student > Doctoral Student | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 31 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 18% |
| Computer Science | 9 | 10% |
| Neuroscience | 6 | 7% |
| Agricultural and Biological Sciences | 5 | 5% |
| Unspecified | 4 | 4% |
| Other | 16 | 18% |
| Unknown | 35 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 27 September 2019.
All research outputs
#2,897,590
of 23,301,510 outputs
Outputs from Frontiers in Genetics
#783
of 12,314 outputs
Outputs of similar age
#60,433
of 340,831 outputs
Outputs of similar age from Frontiers in Genetics
#30
of 313 outputs
Altmetric has tracked 23,301,510 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 12,314 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 93% 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 340,831 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 82% of its contemporaries.
We're also able to compare this research output to 313 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.