Title |
COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection
|
---|---|
Published in |
Journal of Translational Medicine, June 2020
|
DOI | 10.1186/s12967-020-02405-w |
Pubmed ID | |
Authors |
Francesco Messina, Emanuela Giombini, Chiara Agrati, Francesco Vairo, Tommaso Ascoli Bartoli, Samir Al Moghazi, Mauro Piacentini, Franco Locatelli, Gary Kobinger, Markus Maeurer, Alimuddin Zumla, Maria R. Capobianchi, Francesco Nicola Lauria, Giuseppe Ippolito |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 1 | 14% |
Denmark | 1 | 14% |
Unknown | 5 | 71% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 57% |
Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 181 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 29 | 16% |
Student > Bachelor | 23 | 13% |
Student > Master | 22 | 12% |
Researcher | 21 | 12% |
Other | 8 | 4% |
Other | 29 | 16% |
Unknown | 49 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 32 | 18% |
Medicine and Dentistry | 27 | 15% |
Agricultural and Biological Sciences | 9 | 5% |
Computer Science | 9 | 5% |
Immunology and Microbiology | 7 | 4% |
Other | 39 | 22% |
Unknown | 58 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 29 October 2020.
All research outputs
#6,092,544
of 23,164,913 outputs
Outputs from Journal of Translational Medicine
#919
of 4,070 outputs
Outputs of similar age
#130,865
of 398,879 outputs
Outputs of similar age from Journal of Translational Medicine
#26
of 60 outputs
Altmetric has tracked 23,164,913 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
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 has done well, scoring higher than 77% 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 398,879 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 67% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.