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Mendeley readers
Attention Score in Context
| Title |
Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters
|
|---|---|
| Published in |
BMC Systems Biology, January 2014
|
| DOI | 10.1186/1752-0509-8-4 |
| Pubmed ID | |
| Authors |
Austin WT Chiang, Wei-Chung Liu, Pep Charusanti, Ming-Jing Hwang |
| Abstract |
A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 7% |
| India | 1 | 2% |
| Denmark | 1 | 2% |
| Singapore | 1 | 2% |
| Unknown | 39 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 29% |
| Student > Ph. D. Student | 13 | 29% |
| Student > Doctoral Student | 3 | 7% |
| Student > Bachelor | 3 | 7% |
| Student > Master | 3 | 7% |
| Other | 8 | 18% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 22% |
| Biochemistry, Genetics and Molecular Biology | 9 | 20% |
| Computer Science | 6 | 13% |
| Physics and Astronomy | 6 | 13% |
| Engineering | 3 | 7% |
| Other | 6 | 13% |
| Unknown | 5 | 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 16 January 2014.
All research outputs
#18,360,179
of 22,739,983 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#247,110
of 329,839 outputs
Outputs of similar age from BMC Systems Biology
#42
of 58 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% 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 11th percentile – i.e., 11% 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 329,839 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.