| Title |
PTPD: predicting therapeutic peptides by deep learning and word2vec
|
|---|---|
| Published in |
BMC Bioinformatics, September 2019
|
| DOI | 10.1186/s12859-019-3006-z |
| Pubmed ID | |
| Authors |
Chuanyan Wu, Rui Gao, Yusen Zhang, Yang De Marinis |
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 % |
|---|---|---|
| India | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 92 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 21% |
| Student > Ph. D. Student | 12 | 13% |
| Student > Bachelor | 9 | 10% |
| Researcher | 6 | 7% |
| Professor | 5 | 5% |
| Other | 14 | 15% |
| Unknown | 27 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 17% |
| Biochemistry, Genetics and Molecular Biology | 15 | 16% |
| Chemistry | 6 | 7% |
| Agricultural and Biological Sciences | 6 | 7% |
| Medicine and Dentistry | 5 | 5% |
| Other | 14 | 15% |
| Unknown | 30 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 07 September 2019.
All research outputs
#18,028,437
of 23,155,957 outputs
Outputs from BMC Bioinformatics
#5,998
of 7,341 outputs
Outputs of similar age
#238,833
of 340,571 outputs
Outputs of similar age from BMC Bioinformatics
#81
of 92 outputs
Altmetric has tracked 23,155,957 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,341 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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 340,571 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.