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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Time Hierarchies and Model Reduction in Canonical Non-linear Models
|
|---|---|
| Published in |
Frontiers in Genetics, September 2016
|
| DOI | 10.3389/fgene.2016.00166 |
| Pubmed ID | |
| Authors |
Hannes Löwe, Andreas Kremling, Alberto Marin-Sanguino |
| Abstract |
The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems. |
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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 25% |
| Student > Master | 3 | 25% |
| Student > Ph. D. Student | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 33% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Environmental Science | 1 | 8% |
| Earth and Planetary Sciences | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 4 | 33% |
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 02 February 2017.
All research outputs
#17,817,005
of 22,889,074 outputs
Outputs from Frontiers in Genetics
#6,097
of 11,930 outputs
Outputs of similar age
#229,800
of 320,659 outputs
Outputs of similar age from Frontiers in Genetics
#32
of 49 outputs
Altmetric has tracked 22,889,074 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 11,930 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 40th percentile – i.e., 40% 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 320,659 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.