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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A proof for loop-law constraints in stoichiometric metabolic networks
|
|---|---|
| Published in |
BMC Systems Biology, November 2012
|
| DOI | 10.1186/1752-0509-6-140 |
| Pubmed ID | |
| Authors |
Elad Noor, Nathan E Lewis, Ron Milo |
| Abstract |
Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. |
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 % |
|---|---|---|
| Japan | 2 | 67% |
| Peru | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 4% |
| Portugal | 1 | 1% |
| Switzerland | 1 | 1% |
| France | 1 | 1% |
| United Kingdom | 1 | 1% |
| Singapore | 1 | 1% |
| Iran, Islamic Republic of | 1 | 1% |
| Denmark | 1 | 1% |
| Japan | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 73 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 27% |
| Researcher | 23 | 27% |
| Professor > Associate Professor | 8 | 9% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 8 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 36% |
| Biochemistry, Genetics and Molecular Biology | 13 | 15% |
| Engineering | 7 | 8% |
| Mathematics | 6 | 7% |
| Computer Science | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 13 | 15% |
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 13 November 2012.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from BMC Systems Biology
#556
of 1,132 outputs
Outputs of similar age
#116,683
of 193,285 outputs
Outputs of similar age from BMC Systems Biology
#16
of 34 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 46th percentile – i.e., 46% 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 193,285 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.