| Title |
Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome
|
|---|---|
| Published in |
BMC Bioinformatics, January 2019
|
| DOI | 10.1186/s12859-018-2561-z |
| Pubmed ID | |
| Authors |
Kevin Michael Boehm, Bhavneet Bhinder, Vijay Joseph Raja, Noah Dephoure, Olivier Elemento |
X Demographics
The data shown below were collected from the profiles of 14 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 | 9 | 64% |
| Qatar | 1 | 7% |
| United Kingdom | 1 | 7% |
| Unknown | 3 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 50% |
| Members of the public | 5 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 95 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 16% |
| Researcher | 12 | 13% |
| Student > Master | 11 | 12% |
| Student > Bachelor | 11 | 12% |
| Other | 10 | 11% |
| Other | 12 | 13% |
| Unknown | 24 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 20% |
| Agricultural and Biological Sciences | 13 | 14% |
| Medicine and Dentistry | 8 | 8% |
| Computer Science | 8 | 8% |
| Immunology and Microbiology | 6 | 6% |
| Other | 18 | 19% |
| Unknown | 23 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 21 February 2019.
All research outputs
#5,020,301
of 25,040,629 outputs
Outputs from BMC Bioinformatics
#1,756
of 7,641 outputs
Outputs of similar age
#105,753
of 447,140 outputs
Outputs of similar age from BMC Bioinformatics
#52
of 211 outputs
Altmetric has tracked 25,040,629 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,641 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 447,140 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 76% of its contemporaries.
We're also able to compare this research output to 211 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.