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X Demographics
Mendeley readers
Attention Score in Context
| Title |
inTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis
|
|---|---|
| Published in |
BMC Bioinformatics, August 2013
|
| DOI | 10.1186/1471-2105-14-264 |
| Pubmed ID | |
| Authors |
Patrícia Soares, Renato J Alves, Ana B Abecasis, Carlos Penha-Gonçalves, M Gabriela M Gomes, José B Pereira-Leal |
| Abstract |
Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data. |
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 % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 2% |
| Argentina | 1 | 2% |
| Unknown | 63 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 22% |
| Researcher | 13 | 20% |
| Student > Master | 6 | 9% |
| Student > Bachelor | 5 | 8% |
| Professor | 3 | 5% |
| Other | 13 | 20% |
| Unknown | 11 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 29% |
| Medicine and Dentistry | 8 | 12% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Nursing and Health Professions | 4 | 6% |
| Computer Science | 3 | 5% |
| Other | 9 | 14% |
| Unknown | 16 | 25% |
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 21 September 2013.
All research outputs
#14,175,799
of 22,719,618 outputs
Outputs from BMC Bioinformatics
#4,720
of 7,260 outputs
Outputs of similar age
#112,435
of 199,368 outputs
Outputs of similar age from BMC Bioinformatics
#52
of 85 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,260 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 30th percentile – i.e., 30% 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 199,368 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.