| Title |
Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak
|
|---|---|
| Published in |
BMC Infectious Diseases, November 2013
|
| DOI | 10.1186/1471-2334-13-554 |
| Pubmed ID | |
| Authors |
Enrico Lavezzo, Stefano Toppo, Elisa Franchin, Barbara Di Camillo, Francesca Finotello, Marco Falda, Riccardo Manganelli, Giorgio Palù, Luisa Barzon |
| Abstract |
Next generation sequencing (NGS) is being increasingly used for the detection and characterization of pathogens during outbreaks. This technology allows rapid sequencing of pathogen full genomes, useful not only for accurate genotyping and molecular epidemiology, but also for identification of drug resistance and virulence traits. |
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 % |
|---|---|---|
| United States | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 1 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Guatemala | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 57 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 25% |
| Student > Ph. D. Student | 11 | 18% |
| Student > Bachelor | 7 | 12% |
| Student > Doctoral Student | 6 | 10% |
| Student > Master | 5 | 8% |
| Other | 8 | 13% |
| Unknown | 8 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 22% |
| Biochemistry, Genetics and Molecular Biology | 11 | 18% |
| Medicine and Dentistry | 6 | 10% |
| Immunology and Microbiology | 6 | 10% |
| Computer Science | 5 | 8% |
| Other | 6 | 10% |
| Unknown | 13 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 22 November 2013.
All research outputs
#14,638,545
of 23,881,329 outputs
Outputs from BMC Infectious Diseases
#3,716
of 7,931 outputs
Outputs of similar age
#175,881
of 308,070 outputs
Outputs of similar age from BMC Infectious Diseases
#52
of 120 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,931 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 51% 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 308,070 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 120 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 55% of its contemporaries.