You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-211 |
| Pubmed ID | |
| Authors |
Varun Jaiswal, Sree Krishna Chanumolu, Ankit Gupta, Rajinder S Chauhan, Chittaranjan Rout |
| Abstract |
Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially reverse vaccinology (RV) method has enormous potential for identification of protein vaccine candidates (PVCs) from a proteome. The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications for vaccine development. Besides machine learning techniques, those software and web servers have considered only protein's adhesin-likeliness as criterion for identification of PVCs. Several non-adhesin functional classes of proteins involved in host-pathogen interactions and pathogenesis are known to provide protection against bacterial infections. Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 25% |
| United States | 1 | 25% |
| Norway | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 104 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 14% |
| Student > Master | 14 | 13% |
| Student > Bachelor | 12 | 12% |
| Researcher | 11 | 11% |
| Other | 8 | 8% |
| Other | 22 | 21% |
| Unknown | 22 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 28 | 27% |
| Biochemistry, Genetics and Molecular Biology | 20 | 19% |
| Immunology and Microbiology | 10 | 10% |
| Engineering | 5 | 5% |
| Medicine and Dentistry | 3 | 3% |
| Other | 10 | 10% |
| Unknown | 28 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 06 November 2017.
All research outputs
#3,181,593
of 22,713,403 outputs
Outputs from BMC Bioinformatics
#1,176
of 7,259 outputs
Outputs of similar age
#28,689
of 194,634 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 89 outputs
Altmetric has tracked 22,713,403 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,259 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 83% 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 194,634 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 85% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.