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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Stringent DDI-based Prediction of H. sapiens-M. tuberculosis H37Rv Protein-Protein Interactions
|
|---|---|
| Published in |
BMC Systems Biology, December 2013
|
| DOI | 10.1186/1752-0509-7-s6-s6 |
| Pubmed ID | |
| Authors |
Hufeng Zhou, Javad Rezaei, Willy Hugo, Shangzhi Gao, Jingjing Jin, Mengyuan Fan, Chern-Han Yong, Michal Wozniak, Limsoon Wong |
| Abstract |
H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are very important information to illuminate the infection mechanism of M. tuberculosis H37Rv. But current H. sapiens-M. tuberculosis H37Rv PPI data are very scarce. This seriously limits the study of the interaction between this important pathogen and its host H. sapiens. Computational prediction of H. sapiens-M. tuberculosis H37Rv PPIs is an important strategy to fill in the gap. Domain-domain interaction (DDI) based prediction is one of the frequently used computational approaches in predicting both intra-species and inter-species PPIs. However, the performance of DDI-based host-pathogen PPI prediction has been rather limited. |
X Demographics
The data shown below were collected from the profile of 1 X user 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 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 7% |
| France | 1 | 3% |
| Unknown | 26 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 24% |
| Professor > Associate Professor | 4 | 14% |
| Other | 2 | 7% |
| Student > Ph. D. Student | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 9 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 28% |
| Computer Science | 4 | 14% |
| Biochemistry, Genetics and Molecular Biology | 3 | 10% |
| Environmental Science | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 11 | 38% |
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 09 April 2014.
All research outputs
#15,299,491
of 22,753,345 outputs
Outputs from BMC Systems Biology
#644
of 1,142 outputs
Outputs of similar age
#192,611
of 307,397 outputs
Outputs of similar age from BMC Systems Biology
#34
of 61 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 32nd percentile – i.e., 32% 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 307,397 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.