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 |
Comparisons of Shewanella strains based on genome annotations, modeling, and experiments
|
|---|---|
| Published in |
BMC Systems Biology, March 2014
|
| DOI | 10.1186/1752-0509-8-31 |
| Pubmed ID | |
| Authors |
Wai Kit Ong, Trang T Vu, Klaus N Lovendahl, Jenna M Llull, Margrethe H Serres, Margaret F Romine, Jennifer L Reed |
| Abstract |
Shewanella is a genus of facultatively anaerobic, Gram-negative bacteria that have highly adaptable metabolism which allows them to thrive in diverse environments. This quality makes them an attractive bacterial target for research in bioremediation and microbial fuel cell applications. Constraint-based modeling is a useful tool for helping researchers gain insights into the metabolic capabilities of these bacteria. However, Shewanella oneidensis MR-1 is the only strain with a genome-scale metabolic model constructed out of 21 sequenced Shewanella strains. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| United Kingdom | 1 | 1% |
| Unknown | 75 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 27% |
| Student > Ph. D. Student | 17 | 22% |
| Student > Master | 8 | 10% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Other | 15 | 19% |
| Unknown | 7 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 38% |
| Biochemistry, Genetics and Molecular Biology | 16 | 20% |
| Engineering | 10 | 13% |
| Environmental Science | 4 | 5% |
| Computer Science | 3 | 4% |
| Other | 7 | 9% |
| Unknown | 9 | 11% |
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 12 March 2014.
All research outputs
#17,715,061
of 22,747,498 outputs
Outputs from BMC Systems Biology
#770
of 1,142 outputs
Outputs of similar age
#153,768
of 221,230 outputs
Outputs of similar age from BMC Systems Biology
#14
of 21 outputs
Altmetric has tracked 22,747,498 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 27th percentile – i.e., 27% 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 221,230 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 21 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.