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Mendeley readers
Attention Score in Context
| Title |
(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis
|
|---|---|
| Published in |
BMC Systems Biology, November 2013
|
| DOI | 10.1186/1752-0509-7-131 |
| Pubmed ID | |
| Authors |
Fei He, Vincent Fromion, Hans V Westerhoff |
| Abstract |
Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. |
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 % |
|---|---|---|
| Unknown | 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Iran, Islamic Republic of | 1 | 1% |
| United Kingdom | 1 | 1% |
| Singapore | 1 | 1% |
| Unknown | 67 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 35% |
| Researcher | 15 | 21% |
| Professor | 6 | 8% |
| Student > Postgraduate | 6 | 8% |
| Student > Master | 5 | 7% |
| Other | 10 | 14% |
| Unknown | 5 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 43% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Engineering | 7 | 10% |
| Computer Science | 5 | 7% |
| Chemical Engineering | 4 | 6% |
| Other | 4 | 6% |
| Unknown | 13 | 18% |
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 26 November 2013.
All research outputs
#14,182,545
of 22,731,677 outputs
Outputs from BMC Systems Biology
#544
of 1,142 outputs
Outputs of similar age
#173,059
of 301,953 outputs
Outputs of similar age from BMC Systems Biology
#27
of 67 outputs
Altmetric has tracked 22,731,677 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 47th percentile – i.e., 47% 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 301,953 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 67 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 56% of its contemporaries.