The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
| Title |
Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes
|
|---|---|
| Published in |
Genome Medicine, August 2020
|
| DOI | 10.1186/s13073-020-00767-w |
| Pubmed ID | |
| Authors |
Asaf Poran, Dewi Harjanto, Matthew Malloy, Christina M. Arieta, Daniel A. Rothenberg, Divya Lenkala, Marit M. van Buuren, Terri A. Addona, Michael S. Rooney, Lakshmi Srinivasan, Richard B. Gaynor |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| El Salvador | 1 | 11% |
| Unknown | 8 | 89% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 44% |
| Scientists | 2 | 22% |
| Science communicators (journalists, bloggers, editors) | 2 | 22% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 174 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 18% |
| Student > Bachelor | 24 | 14% |
| Student > Ph. D. Student | 16 | 9% |
| Other | 15 | 9% |
| Student > Master | 12 | 7% |
| Other | 21 | 12% |
| Unknown | 54 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 14% |
| Medicine and Dentistry | 22 | 13% |
| Immunology and Microbiology | 16 | 9% |
| Agricultural and Biological Sciences | 11 | 6% |
| Nursing and Health Professions | 10 | 6% |
| Other | 34 | 20% |
| Unknown | 56 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 13 April 2023.
All research outputs
#2,170,129
of 26,363,900 outputs
Outputs from Genome Medicine
#473
of 1,643 outputs
Outputs of similar age
#56,393
of 429,370 outputs
Outputs of similar age from Genome Medicine
#8
of 24 outputs
Altmetric has tracked 26,363,900 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,643 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.4. This one has gotten more attention than average, scoring higher than 71% 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 429,370 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 86% of its contemporaries.
We're also able to compare this research output to 24 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 66% of its contemporaries.