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Mendeley readers
Attention Score in Context
| Title |
Optimal enumeration of state space of finitely buffered stochastic molecular networks and exact computation of steady state landscape probability
|
|---|---|
| Published in |
BMC Systems Biology, March 2008
|
| DOI | 10.1186/1752-0509-2-30 |
| Pubmed ID | |
| Authors |
Youfang Cao, Jie Liang |
| Abstract |
Stochasticity plays important roles in many molecular networks when molecular concentrations are in the range of 0.1 muM to 10nM (about 100 to 10 copies in a cell). The chemical master equation provides a fundamental framework for studying these networks, and the time-varying landscape probability distribution over the full microstates, i.e., the combination of copy numbers of molecular species, provide a full characterization of the network dynamics. A complete characterization of the space of the microstates is a prerequisite for obtaining the full landscape probability distribution of a network. However, there are neither closed-form solutions nor algorithms fully describing all microstates for a given molecular network. |
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 % |
|---|---|---|
| Norway | 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 4% |
| United States | 1 | 4% |
| Unknown | 24 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 31% |
| Student > Ph. D. Student | 6 | 23% |
| Student > Bachelor | 3 | 12% |
| Professor | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 2 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 42% |
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Mathematics | 2 | 8% |
| Physics and Astronomy | 2 | 8% |
| Business, Management and Accounting | 1 | 4% |
| Other | 4 | 15% |
| Unknown | 1 | 4% |
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 14 March 2013.
All research outputs
#17,682,134
of 22,701,287 outputs
Outputs from BMC Systems Biology
#770
of 1,142 outputs
Outputs of similar age
#74,546
of 81,187 outputs
Outputs of similar age from BMC Systems Biology
#7
of 7 outputs
Altmetric has tracked 22,701,287 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 81,187 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.